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Appare necessario, per quell’indispensabile ripristino delle condizioni della fiducia, avere la massima attenzione alle diversità di ogni tipologia di amministrazione, dal piccolo comune al grande ente centrale, mettendo in evidenza sempre le tante eccellenze presenti, nate spesso dell’impegno di una unità organizzativa e dei suoi dirigenti, che devono trovare pubblicità, apprezzamento dell’opinione pubblica, effettivi riconoscimenti da parte del governo centrale. Anche appoggiandosi a agenzie indipendenti, il governo dovrebbe curare un catalogo ricco e aggiornato di “buoni esempi”, che porti con sé anche la strumentazione amministrativa utile per replicarlo.

Oh no I’m sure any delta is brighter than an epsilon like those. That’s one of the wonderful things about being a gamma. We’re not too stupid and we’re not too bright to be a gamma is to be just right

Rather than imagine a timeless world of connection and multiple paths, the Stream presents us with a single, time ordered path with our experience (and only our experience) at the center.

Trump’s digital strategy, Singer and Brooking argue, is not unlike militant groups and street gangs that leverage the viral web to tell a compelling story about policy, religious dogma, or their own perceived fearsomeness, all in an engaging voice, while repeatedly targeting exactly the right audience to trigger a dopamine response or sheer terror, both online and IRL. "To 'win' the internet, one must learn how to fuse these elements of narrative, authenticity, community, and inundation," Singer and Brooking write. "And if you can 'win' the internet, you can win silly feuds, elections, and deadly serious battles."

In 1968, two psychologists wrote a paper theorizing that computers could become communications devices. The US Department of Defense ran with the idea, and in 1969 the precursor of the internet as we know it today, the military-operated ARPANET, went live. The National Science Foundation took over in the 1980s before business began to dominate in the 90s, at which point, things started to grow in exponential leaps. There were 28,000 internet users in 1987, according to Singer and Brooking. Today, there are billions.

Trump's unlikely rise to the White House was symptomatic of social, political, and technological trends decades in the making—trends that gave rise to the internet and social media and which, in turn, transformed the way we control, spy on, and kill each other.

All tribes need tribal leaders, who in turn need loyalty. Followers of Corbyn and Trump will both detest the comparison, but note how both have the merch, the chants, the hagiography. They’re radically different, but both are products of the tribalism that social media has accidentally brought about.

My relationship is a lot healthier with blogs that I visit when I please. This is another criticism I have with RSS as well—I don’t want my favorite music blog sending me updates every day, always in my face. I just want to go there when I am ready to listen to something new. (I also hope readers to my blog just stop by when they feel like obsessing over the Web with me.)

Our empirical example also highlighted the value of achieving virtual temporal symmetry for members of a geographically dispersed community. As electronic me­dia become increasingly central to organizational life, in­dividuals may use asynchronous media in various ways to shape devices of virtual symmetry that help them co­ordinate across geographical distance and across multiple temporal structures. This suggests that when studying the use of electronic media, researchers should pay attention to the conditions in which virtual temporal symmetry may be enacted to coordinate distributed activities, and with what consequences. Interesting questions for empirical research include the following. As work groups in orga­nizations become more geographically dispersed and/or more dependent on electronic media, do members enact virtual temporal symmetry for certain purposes? If so, for which types of purposes? And how? If not, how do such work groups achieve temporal coordination?

social ecology formally emerged with the work of Murray Bookchin

the critique of a thing is inherent in the alternative presented

We refer to the plural

About

tri-fold pamphlet created around 2007

This approach, I believe, works well for digital ethics, where we try to articulate rules that govern how we interact with each other through digital technologies. For example, when social media emerged, there was no fixed rule about when it is appropriate to tag someone in a picture and when it isn’t. So we figured out a netiquette and ethical norms as we were going along, based on experience, existing norms, insights from experts etc. There still might be areas of disagreement, but I would argue that overall we have come to an understanding of what is acceptable and what isn’t on this issue, and these norms are passed on to new users of social media.

Phillip Kitcher, in the introduction of The Ethical Project describes the project of this pragmatic naturalism as follows: “Ethics emerges as a human phenomenon, permanently unfinished. We, collectively, made it up, and have developed, refined, and distorted it, generation by generation. Ethics should be understood as a project --the ethical project-- in which we have been engaged for most of our history as a species.” This a functionalist view sees ethics as a set of guidelines that make communal living possible. A successful ethical system is one that can fulfill this function.

For a pragmatist, documenting this change and questioning what perpetuated it in order to better understand our current norm is the more interesting endeavor. From this understanding, ethical guidelines can be crafted, but the descriptive process precedes the prescriptive one.

According to pragmatics, our attitudes and norms change in response to societal changes. For example, in an episode of Mad Men a guest at a party could be seen slapping a child that wasn’t his. It was one of the many (and one of the milder) examples in which the show’s creators’ reminded their audience that in the 1960s different rules governed social interactions.

The social foci hypothesis predicts that links are more likely to form among individuals who, for example, are classmates, co-workers, or go to the same gym (they share a social foci). The triadic closure hypothesis predicts that links are more likely to form among individuals that share “friends” or acquaintances. Finally, the homophily hypothesis predicts that links are more likely to form among individuals who share social characteristics, such as tastes, cultural background, or physical appearance (Lazarsfeld and Merton 1954), (McPherson et al. 2001).

merican public life has become increasingly ideologically segregated as newspapers have given way to screens. But societies have experienced extremism and fragmentation without the assistance of Silicon Valley for centuries. And the polarization in the US began long ago, with the rise of 24-hour cable news. So just how responsible is the internet for today’s divisions? And are they really as bad as they seem?

Social media is well-understood to be contributing to identity politics, but I’d argue it’s contributing to something deeper: identity paralysis. This condition is one in which we have a forced awareness of how everything we say and do — even the seemingly inconsequential, like the shoes we wear, or the airline we fly — reflects on us.

we can’t just recreate the same thing we’re trying to escape, and we can’t expect the solution to be precisely as easy on us as the problem was.

Just like in real life, where your bar trivia team doesn’t really overlap with your work softball team or your church bowling league, all of your online communities gathered in their own places, ones best suited to them, and you didn’t have to act as all facets of yourself simultaneously when trying to only interact with one.

You might have seen the hashtag #BlackLivesMatter in the previous step. In this 6-minute video, #BlackTwitter after #Ferguson, we meet activists who were involved in the movement and learn about their own uses of Twitter as a platform of protest. Hashtags, when used like this, can be extremely complex in the way they represent ideas, communities and individuals.

To start you thinking, here’s a quote from lead educator Jean Burgess. Jean considers how Twitter has changed since 2006 and reflects on her own use of the platform in the context of changing patterns of use. In response to the suggestion that Twitter is a dying social media platform, Jean states that: the narratives of decline around the place at the moment […] have to do with a certain loss of sociability. And to those of us for whom Twitter’s pleasures were as much to do with ambient intimacy, personal connections and play as they were to do with professional success theatre, celebrity and breaking news, this is a real, felt loss: sociability matters.

Leaming viewed as situated activity has as its central defining characteristic a process that we call legitimate peripheral par­ticipation. By this we mean to draw attention to the point that learners inevitably participate in communities of practitioners and that the mastery of knowledge and skill requires newcom­ers to move toward full participation in the sociocultural practices of a community.

"Legitimate peripheral participation" provides a way to speak about the relations between newcom­ers and old-timers, and about activities, identities, artifacts, and communities of knowledge and practice. It concerns the process by which newcomers become part of a community of practice. A person's intentions to learn are engaged and the meaning of learning is configured through the process of be­coming a full participant in a sociocultural practice. This so­cial process includes, indeed it subsumes, the learning of knowledgeable skills.

Thus, an enacted environment has both a public and a private face. Publicly, it is a construction that is usually visible to observers other than the actor. Privately, it is a map of if-then assertions in which actions are related to out- comes. These assertions serve as expectations about what will happen in the future.

At the heart of enactment is the idea that cognition lies in the path of the action. Action precedes cognition and focuses cognition. The sensemaking sequence implied in the phrase, ‘How can I know what I think until I see what I say?’ involves the action of talking, which lays down traces that are examined, so that cognitions can be inferred. These inferred cognitions then become pre- conceptions which partially affect the next episode of talk, which means the next set of traces deposited by talk are affected partially by previous labels and partially by current context. These earlier inferences also affect how the next episode of talk is examined and what is seen.

Another way to use a classification system is to consider if there are other possible values that could be used for a given dimension.

For researchers looking for new avenues within human computation, a starting point would be to pick two dimensions and list all possible combinations of values.

These properties formed three of our dimensions: motivation, human skill, and aggregation.

A subtle distinction among human computation systems is the order in which these three roles are performed. We consider the computer to be active only when it is playing an active role in solving the problem, as opposed to simply aggregating results or acting as an information channel. Many permutations are possible.

The classification system we are presenting is based on six of the most salient distinguishing factors. These are summarized in Figure 3.

"... groups of individuals doing things collectively that seem intelligent.” [41]

Data mining can be defined broadly as: “the application of specific algorithms for extracting patterns from data.” [17]

“... applications and services that facilitate collective action and social interaction online with rich exchange of multimedia information and evolution of aggregate knowledge...” [48]

The intersection of crowdsourcing with human computation in Figure 1 represents applications that could reasonably be considered as replacements for either traditional human roles or computer roles.

“Crowdsourcing is the act of taking a job traditionally performed by a designated agent (usually an employee) and outsourcing it to an undefined, generally large group of people in the form of an open call.” [24

modern usage was inspired by von Ahn’s 2005 dissertation titled "Human Computation" [64] and the work leading to it. That thesis defines the term as: “...a paradigm for utilizing human processing power to solve problems that computers cannot yet solve.”

When classifying an artifact, we consider not what it aspires to be, but what it is in its present state.

human computation does not encompass online discussions or creative projects where the initiative and flow of activity are directed primarily by the participants’ inspiration, as opposed to a predetermined plan designed to solve a computational problem.

Human computation is related to, but not synonymous with terms such as collective intelligence, crowdsourcing, and social computing, though all are important to understanding the landscape in which human computation is situated.

Because of both the content that people upload and the behavioral traces that they leavebehind, social network sites have unprecedented quantities of data concerning humaninteraction. This presents unique opportunities and challenges. On one hand, SNSs offera vibrant “living lab” and access to behavioral data at a scale inconceivable to manysocial scientists. On the other, the data that are available present serious research ethicsquestions and introduce new types of biases that must be examined (boyd and Crawford2012)

For those of us who believe that social network sites are socio-technical systems, in whichsocial and technical factors shape one another, failing to describe the site under studyignores the fact that the technological constraints and affordances of a site will shapeuser practices and that social norms will emerge over time. Not including informationabout what the feature set was at the time of data collection forecloses the possibility ofidentifying patterns that emerge over time and through the accumulated scholarshipacross a range of sites and user samples. Unfortunately, because they have no knowledgeabout how things will continue to evolve and which features will becomeimportant to track, researchers may not be able to identify the salient features to reportand may struggle with devoting scarce publication space to these details, but this doesn’tundermine the importance of conscientious consideration towards describing the artifactbeing analyzed.

In order to produce scholarship that will be enduring, the onus is on social mediaresearchers to describe the technological artifact that they are analyzing with as muchcare as survey researchers take in describing the population sampled, and with as muchdetail as ethnographers use when describing their field site. This is not to say thatresearchers must continue to describe technologies as if no one knows what they are—weare beyond the point where researchers must explain how electronic mail or “email” islike or unlike postal mail. But, rather, researchers must clearly describe the socio-technical context of the particular site, service, or application their scholarship isaddressing. In addition to attending to the technology itself, and the interchange betweentechnical and social processes, we believe SNS researchers should make a concertedeffort to include the date of data collection and to describe the site at the moment of datacollection and the relevant practices of its users. These descriptions will enable laterresearchers to synthesize across studies to identify patterns, much in the same wayreporting exact effect sizes allows for future meta-analyses

One key challenge of studying social media is that designers of these tools are innovatingat a very rapid timeframe and often with little advance notice. Given the rapidly changinginfrastructure and the timeframe of academic publishing, the site at the time of datacollection is likely to be very different from its incarnation at the point of publication.

Because of howpeople's position within the SNS shapes their experiences of it, activity-centric analysesrequire contextualization and translation, not unlike what social scientists studyingdiffering cultural practices have had to do for decades.

What oneexperiences on SNSs and the content to which one is exposed differs depending on thestructure of one's network, a user's individual preferences and history, and her activitiesat that moment.

By far the most pressing challengefor SNS scholars lies in the rapid pace at which innovations and technical changes areimplemented in this space. For scholarship in this arena to develop, SNS researchersneed to be mindful of the ways in which these sites evolve over time and the effects thismay have on the interpersonal, psychological, and sociological processes they arestudying.

What makes “social media” significant as a category is not the technology, butrather the socio-technical dynamics that unfolded as millions of people embraced thetechnology and used it to collaborate, share information, and socialize. Popular genres ofsocial media integrated the public nature of interest-driven CMC with the more intimatedynamics of interpersonal CMC.

All SNSs support multiple modes of communication: one-to-many and one-to-one,synchronous and asynchronous, textual and media-based

Many of the weak tie relationships articulatedon SNSs would fade away were it not for the ease with which people can communicate,share, and maintain simple connections. For this reason, this new definition positionssocial network sites first and foremost as a communication platform, while alsohighlighting the importance of sharing content, typically consumed through a stream.

A social network site is anetworked communication platformin which participants1) haveuniquely identifiable profilesthat consist of user-supplied content, contentprovided by other users, and/or system-level data; 2) canpublicly articulateconnectionsthat can be viewed and traversed by others; and 3) can consume,produce, and/or interact withstreams of user-generated contentprovided by theirconnections on the site.

As social network sites have become mainstream, traversing the connections betweenpeople to view profiles is no longer the sole—or, even primary—way of participation.Content is surfaced through streams, and each piece of content is embedded withnumerous links to other content nuggets.

Yet, one significant shift has unfolded: the traversability ofconnections has become more important for machines than users. As APIs make thesocial graph available to broader audiences, algorithms are being designed to traversethe graph and learn about the individual nodes’ relationship to one another.

The ability to see—andtraverse—others’ contact lists was innovative and important in several ways. From anadoption perspective, it enabled users to find shared contacts easily, thus lowering thebarriers to initiating contact with other users and enabling users to harness networkeffects more easily. From a social perspective, it allowed people to easily see therelationships between others, to reconnect with old friends and acquaintances, and totravel through the network in a way that enhanced social interactions.

The rise of open APIs and developer platforms meant that these collections of articulatedcontacts became valuable in contexts outside that particular SNS. Engineers andentrepreneurs alike began talking about the “social graph”—the global network oflinkages between all individuals within a system (Fitzpatrick and Recordon2007). Thislanguage emerged at a time when commercial entities began to believe that the socialgraph hadvalue beyond the individual's relationship with a given social networksite.

As SNSs became more popular with a wider range ofindividuals, many individuals’ contact lists became more diverse as these users Friendedpeople representing a range of contexts (family, professional contacts, church members,etc.). This growing diversity has contributed to cases of “context collapse,” whichdescribes the ways in which individuals that we know from different social contexts cometogether in SNSs in potentially uncomfortable ways (Marwick and boyd2011)

For users, these connections represent what sociologistsrefer to as a person'ssocial network—the collection of social relations of varyingstrengths and importance that a person maintains

Earlier communication tools enabled individuals to create a private list ofcontacts (for instance a buddy list on instant messaging), to establish a group of contactsthat were shared by others (such as a listserv membership list), or to publish a list ofrelated links (such as a blogroll), but SNSs extended the practice of creating a publiclyvisible, personally curated list of contacts and made it a mainstream practice.

Streams of quotidian,ephemeral content encourage people to participate more in that they provide an initialartifact around which others can engage. Features that support actions associated withstatus updates—the ability to post comments to, share, or register interest in an update—also encourage a stream of activity that is prompted by an update but often takes on a lifeof its own in the central stream. Today's SNSs are more like news aggregators than theyare like profile-based contexts, even if the algorithm for displaying content is quiteobfuscated.

In boyd and Ellison (2007), we attempted to stabilize the discussion by offeringa definition of social network sites:web-based services that allow individuals to (1) construct a public or semi-publicprofile within a bounded system, (2) articulate a list of other users with whom theyshare a connection, and (3) view and traverse their list of connections and thosemade by others within the system.

hus it becomes possible to see how ques-tions around data use need to shift from asking what is in the data, to include discussions of how the data is structured, and how this structure codifies value systems and social practices, subject positions and forms of visibility and invisi-bility (and thus forms of surveillance), along with the very ideas of crisis, risk governance and preparedness. Practices around big data produce and perpetuate specific forms of social engagement as well as understandings of the areas affected and the people being served.

Big data is not just about knowing more. It could be – and should be – about knowing better or about changing what knowing means. It is an ethico- episteme-ontological- political matter. The ‘needle in the haystack’ metaphor conceals the fact that there is no such thing as one reality that can be revealed. But multiple, lived are made through mediations and human and technological assemblages. Refugees’ realities of intersecting intelligences are shaped by the ethico- episteme-ontological politics of big data.

Burns (2015) builds on this to investigate how within digital humanitarianism discourses, big data produce and perform subjects ‘in need’ (individuals or com-munities affected by crises) and a humanitarian ‘saviour’ community that, in turn, seeks answers through big data

Crises are often not a crisis of information. It is often not a lack of data or capacity to analyse it that prevents ‘us’ from pre-venting disasters or responding effectively. Risk management fails because there is a lack of a relational sense of responsibility. But this does not have to be the case. Technologies that are designed to support collaboration, such as what Jasanoff (2007) terms ‘technologies of humility’, can be better explored to find ways of framing data and correlations that elicit a greater sense of relational responsibility and commitment.

In some ways this constitutes the production of ‘liquid resilience’ – a deflection of risk to the individuals and communities affected which moves us from the idea of an all-powerful and knowing state to that of a ‘plethora of partial projects and initiatives that are seeking to harness ICTs in the service of better knowing and governing individuals and populations’ (Ruppert 2012: 118)

Indeed, as Chandler (2015: 9) also argues, crowdsourcing of big data does not equate to a democratisation of risk assessment or risk governance:

ut Burns finds that humanitarian staff often describe the local communities and ‘crowds’ as the ‘eyes, ears and sensors’ of UN staff, which does not index a genuine collaborative relationship. He states: ‘In all these cases, the discourse talks of putting local people “in the driving seat” when in reality the direction of the journey has already been decided’ (Burns 2015: 48). Burns (2015: 42) also notes that this leads to a transformation of social responsibility into individual responsibility.Neoliberalism’s promotion of free market norms is therefore much more than the simple ideology of free market economics. It is a specific form of social rule that institutionalises a rationality of competition, enterprise indi-vidualised responsibility. Although the state ‘steps back’ and encourages the free conduct of individuals, this is achieved through active intervention into civil society and the opening up of new areas to the logic of private enter-prise and individual initiative. This is the logic behind the rise of resilience

The UNHCR has even called for the refugees themselves to also develop their own data solutions and ideas (see Palmer 2014) as a way to help build their ideologies into the data infrastructures and thus bring their prisms into view. This could create a richer situational awareness and a better ability to understand and deal with unfolding and future crises by supporting resilient communities through giving them the means of data producing and sharing

Doing so switches the discourse from vulnerability, where there is a need for external protection mobilised from above to come in and rescue the refugees, to one of resilience, where self- sufficiency and autonomy are part of the equation (Meier 2013).

Yet, at the same time as power is exercised by both the state and corporations, power is gathering from the bottom up in new ways. In disaster response, a dynamic interplay between publics and experts is captured by the concept of social collective intelligence (Büscher et al. 2014); a disruptive innovative force that is challenging the social, economic, political and organisational practices that shape disaster response.

Since the data is already being collected on a regular basis by ubiquitous private firms, it is thought to contain information that will increase opportunities for intelligence gathering and thereby security. This marks a shift from surveillance to ‘dataveillance’ (van Dijck 2014), where the impetus for data processing is no longer motivated by specific purposes or suspicions, but opportunistic discovery of anomalies that can be investigated. For crisis management this could mean benefits such as richer situation awareness, increased capacity for risk assess-ment, anticipation and prediction, as well as more agile response

lthough Snowden’s revelations shocked the world and prompted calls for a public debate on issues of privacy and transparency

While seemingly avoiding the traps of exerting top- down power over people the state does not yet have formal control over, and simultaneously providing support for self- determination and choice to empower individuals for self- sufficiency rather than defining them as vulnerable and passive recipients of top- down protection (Meier 2013), tying individual aid to mobile tracking puts refugees in a situation where their security is dependent upon individual choice and the private sector. Apart from disrupting traditional dynamics of responsibility for aid and protection, public–private sharing of intel-ligence brings new forms of dataveillance

However, with these big data collections, the focus becomes not the individu-al’s behaviour but social and economic insecurities, vulnerabilities and resilience in relation to the movement of such people. The shift acknowledges that what is surveilled is more complex than an individual person’s movements, communica-tions and actions over time.

Andrejevic and Gates (2014: 190) suggest that ‘the target becomes the hidden patterns in the data, rather than particular individuals or events’. National and local authorities are not seeking to monitor individuals and discipline their behaviour but to see how many people will reach the country and when, so that they can accommodate them, secure borders, and identify long- term social out-looks such as education, civil services, and impacts upon the host community (Pham et al. 2015).

as boyd and Crawford argue, ‘without taking into account the sample of a data set, the size of the data set is meaningless’ (2012: 669). Furthermore, many tech-niques used by the state and corporations in big data analysis are based on probabilistic prediction which, some experts argue, is alien to, and even incom-prehensible for, human reasoning (Heaven 2013). As Mayer-Schönberger stresses, we should be ‘less worried about privacy and more worried about the abuse of probabilistic prediction’ as these processes confront us with ‘profound ethical dilemmas’ (in Heaven 2013: 35).

Second, this tracking and tracing of refugees has become a deeply ambiguous process in a world riven by political conflict, where ‘migration’ increasingly comes to be discussed in co- location with terrorism.

Surveillance studies have tracked a shift from discipline to control (Deleuze 1992; Haggerty and Ericson 2000; Lyon 2014) exemplified by the shift from monitoring confined populations (through technologies such as the panopticon) to using new technologies to keep track of mobile populations.

As Coyle and Meier (2009) argue, disasters are often seen as crises of information where it is vital to make sure that people know where to find potable water, how to ask for help, where their relatives are, or if their home is at risk; as well as providing emergency response and human-itarian agencies with information about affected populations. Such a quest for information for ‘security’, in turn, provides fertile ground for a quest for technological solutions, such as big data, which open up opportunities for the extended surveillance of everyday life. The assumption is that if only enough information could be gathered and exchanged, preparedness, resilience and control would follow. This is particularly pertinent with regard to mobile pop-ulations (Adey and Kirby 2016)

hird, at this juncture, control is being equated with visibility and visibility with personal security. But how these individuals are made visible matters for both privacy and security, let alone the politics of conflating refugees, migration and terrorism. Indeed, working with specific data framing mechanisms affects how the causes and effects of disasters are identified and what elements and people are considered (Frickel 2008

First, there is a double dynamic to the generation of data in the refugee crisis.

Datafication refers to the fact that ‘we can now capture and calculate at a much more comprehensive scale the physical and intangible aspects of existence and act on them’ (Mayer- Schönberger and Cukier 2013: 97

There is an uneasy coming together of diverse computational and human intelligences in these intersections, and the ambiguous nature of intelligence – understood, on the one hand, as a capacity for perceiving, learning and under-standing and, on the other, as information obtained for strategic purposes – marks complex relationships between ‘good’ and ‘dark’ aspects of big data, surveil-lance and crisis management.

The goal of this framework is to envision afuture of crowd work that cansupport more complex, creative, and highly valued work. At the highest level, a platformis needed for managing pools of tasksandworkers. Complex tasks must be decomposed into smaller subtasks, each designed with particular needs and characteristics which must be assignedto appropriate groups of workerswho themselves must be properly motivated, selected(e.g., through reputation), and organized (e.g., through hierarchy). Tasks may be structured through multi-stage workflowsin which workers may collaborateeither synchronously or asynchronously. As part of this, AImay guide (and be guided by) crowd workers. Finally, quality assuranceis needed to ensure each worker’s output is of high quality and fits together.

n human computation, people act as computational components and perform the work that AI systemslack the skillstocomplete

A promising approach that addresses some worker output issues examines the way that workers do their work rather than the output itself, using machine learning and/or visualization to predict the quality of a worker’s output from their behavior [119,120]

Of the research foci, quality control has arguably received the most attention so far. Approaches for quality control largely fall into two camps: up-front task design and post-hoc result analysis. Task design aimsto design tasks that are resistant to low-quality work.

Many tasks worth completing require cooperation –yet crowdsourcing has largely focused on independent work. Distributed teams have always facedchallenges in cultural differences and coordination[60], but crowd collaboration now must createrapport over much shorter timescales(e.g., one hour) and possibly wider culturalor socioeconomic gaps

Finally, it will be amajor research undertaking to invent and describe the tasks and techniques that succeed with synchronous collaboration

The two core challenges for realtime crowdsourcing will be 1) scaling upto increased demand for realtime workers, and 2) making workers efficient enough to collectively generateresultsahead of time deadlines.

Volunteer crowdsourcing platforms have evolved their own hierarchies and decision-making processes [104,156], appropriating techniques from other online communities where appropriate [101]. Most paid approaches have workers make hierarchical decisions collectively: for example, task decomposition and integration[75,80],quality oversight of each others’ contributions[78,100], and leader elections to represent collective opinions[83].

Complex tasks have dependencies, changing requirements, and require multiple types of expertise.

n the sections below, we survey and analyze the 12research focithat comprise our model. First, we consider the future of the work processesand how the workis organized and accomplished. Second, we consider the integration of crowd work and computation, including the symbiosis between human cognition, artificial intelligence(AI), and computationally-enabled crowd platforms. Finally, we consider crowd workers and how we can develop jobs, reputation systems, motivations, and incentives that will benefit them.

Unlike traditional organizations in which workers possess job security and managers can closely supervise and appropriately reward or sanction workers, or distributed computing systems in which processors are usually highly reliable, crowd work poses uniquechallenges for both workers and requestersranging fromjob satisfactiontodirection-setting, coordination, and quality control.

These same requirements exist in distributed computing, in which tasks need to be scheduled so that they can be completed in the correct sequence and in a timely manner, with data being transferred between computing elements appropriately.

However, crowd work can bea double-edged sword,equally capable of enhancing or diminishing the quality of workers’ lives.We maysee echoes of past labor abuses in globally distributed crowd work: extremely low pay for labor,with marketplaces such as Amazon’s Mechanical

We focus this paper on paid,onlinecrowd work, which we define here as the performance of tasks online by distributed crowd workers who are financially compensated by requesters(individuals, groups, or organizations). In this sense, crowd work is a socio-technical work systemconstituted through a set of relationships that connect organizations, individuals, technologies and work activities

A variety of terminology is currently used in regard to crowds, e.g. crowdsourcing, collective intelligence, human computation, serious games,peer production, and citizen science

A related series of studies have sought to unpack the dynamics of collabo-ration and to understand which features of peer productions support the cre-ation of higher quality content. This topic has been studied especially closelyin the case of Wikipedia, where particular organizational attributes, routines,norms, and technical features impact the quality of individual contributionsas well as the final, collaborative product.

A more fruitfulapproach considers variation in peer production success to understand whenand where it works better and worse.

Just as peer produced goods vary in their nature and form, there is alsoenormous variation between and within projects in terms of the dimensionsalong which quality might be evaluated. In the case of Wikipedia, scholarshave assessed the encyclopedia in terms of factual accuracy, scope of coverage,political bias, expert evaluation, and peer evaluation – often drawing differentconclusions about the quality of Wikipedia or particular articles.

Although this hasconstituted an inconvenient fact in peer production practice, it also reflects animportant opportunity for future research. By focusing only on the projectsthat successfully mobilize contributors, researchers interested inwhenpeerproduction occurs or the reasonswhyit succeeds at producing high qualityoutputs have systematically selected on their dependent variables. An impor-tant direction for peer production research will be to study these failures.

Infollowing these three paths, scholars have begun to consider variation withinpeer production projects to understand when and why peer production leadsto different kinds of high quality outputs

Both for-profit andnon-profit organizations that have incorporated peer production models havethrived in the networked environment, often overcoming competition frommore traditional, market- and firm-based models.

Recent work hasbegun to probe more deeply into different dimensions along which qualitycan be conceptualized and measured. This new scholarship has given rise toa more nuanced understanding of the different mechanisms through whichhigh quality resources arise, and founder, in peer production.

Peer production successfully elicits contributions from diverse individu-als with diverse motivations – a quality that continues to distinguish it fromsimilar forms of collective intelligence

Resolving the tensions between different motivations and incentives presentsa design challenge for peer production systems and other collective intelli-gence platforms. The complex interdependence of motivations, incentive sys-tems, and the social behaviors that distinct system designs elicit has led Krautand Resnick (2012) to call for evidence-based social design and Benkler (2009,2011) for cooperative human system design.

Evidence from this newer body of research shows that motivations are di-versewithincontributors and that different contributors have different mixesof motivations.

The most important insight provided by some of this newer workis that contributors act for different reasons, and that theories based on a sin-gle uniform motivational model are likely to mischaracterize the motivationaldynamics.

In particular, these neweraccounts have focused on social status, peer effects, prosocial altruism, groupidentification, and related social psychological dimensions of group behavior

hat said, a growing number of stud-ies also suggest that these motives interact with each other in unpredictableways and, as a result, are vulnerable to “crowding out” when the introduc-tion of extrinsic incentives undermines intrinsic motivation

Other foundational research on motivation in peer production by Lernerand Schankerman (2010) and others has explored why organizations, firmsand governments, rather than individual users, choose to participate in opensource software.

Despite their differences in emphasis,scope, and genre, all of these surveys support the claim that motivations inpeer production are diverse and heterogeneous.

Frequently cited motivations in foundational work by theseauthors, von Hippel and von Krogh (2003), von Krogh (2003), and others in-cluded: the use value of the software to the contributing developer; the hedo-nic pleasure of building software; the increased human capital, reputation,or employment prospects; and social status within a community of peers.Other early accounts analyzing examples of peer production beyond FLOSSsuggested additional motivations. For example, Kollock (1999) emphasizedreciprocity, reputation, a sense of efficacy, and collective identity as salientsocial psychological drivers of contribution to online communities and fo-rums.

A second quality of peer production that challenged conventional economictheories of motivation and cooperation was the absence of clear extrinsic in-centives like monetary rewards. Traditional economic explanations of behav-ior rely on the assumption of a fundamentally self-interested actor mobilizedthrough financial or other incentives. In seeking to explain how peer produc-tion projects attract highly skilled contributors without money, much of theliterature on peer production has focused on questions of participant moti-vation.

A newer wave of work has stepped back from this approachand sought to explain how multiple motivational “vectors” figure in the cre-ation of common pool resources online – an approach that underscores a coreadvantage of peer production in its capacity to enable action without requir-ing translation into a system of formalized, extrinsic, carrots and sticks.

Future workcan also begin to address questions of whether, how, and why peer produc-tion systems have transformed some existing organizational fields more pro-foundly than others. An empirically-informed understanding of when andwhere organizational practices drawn from peer production provide efficientand equitable means to produce, disseminate, and access information can pro-vide social impact beyond the insights available through the study of any in-dividual community

By structuring design changes as exper-iments, these studies make credible causal claims about the relationship oforganizational structure and project outcomes that previous work struggledto establish. By intervening in real communities, these efforts achieve a levelof external validity that lab-based experiments cannot

Similar cross-organization studies in other areas of peer production, orstudies comparing across differenttypesof peer production, have remainedchallenging and rare. One difficulty with comparative work across organiza-tions, in general, is designing research capable of supporting inference intothe causes of organizational success and failure

Although some of the earliest theories of the organization of peer pro-duction celebrated the phenomena as non-hierarchical, more recent work hasquestioned both the putative lack of hierarchy and its purported benefits (e.g.,Kreiss et al., 2011).

More recent work on organizational aspects of peer production has begunto question the “stylized facts” that prevailed in earlier research.

This research built on earlier work showing that contrib-utors to bulletin boards, newsgroups, forums, and related systems adopteddurable “social roles” through their patterns of contribution (e.g., Fisher et al.,2006) – an approach that was subsequently applied to Wikipedia by Welseret al. (2011) and McDonald et al. (2011)

A large body of descriptive work has also sought to characterize organi-zational dimensions of Wikipedia and the practices of its contributors.

Much of the earliest empirical research inductively sought to describe thestructure and organization of FLOSS communities

Other foundational accounts, like Moglen (1999) and Weber (2004),attended to the emergence of informal hierarchies and governance arrange-ments within communities.

Peer productioncould, Benkler argued, outperform traditional organizational forms underconditions of widespread access to networked communications technologies,a multitude of motivations driving contributions, and non-rival informationcapable of being broken down into granular, modular, and easy-to-integrate

Initial scholarship on the organization of peer production emphasized the-oretical distinctions between peer production, bureaucracy, and transactioncost explanations of firms and markets.

Indeed, peer production com-munities perform all of the “classical” organizational functions like coordina-tion, division of labor, recruitment, training, norm creation and enforcement,conflict resolution, and boundary maintenance – but do so in the absence ofmany of the institutions associated with more traditional organizations.

In the rest of this chapter, we describe the development of the academicliterature on peer production and collective intelligence in three areas – or-ganization, motivation, and quality. In each area, we introducefoundationalworkconsisting primarily of earlier scholarship that sought to describe peerproduction and establish its legitimacy. Subsequently, we characterize work,usually more recent, that seeks to pursuenew directionsand to derive morenuanced analytical insights. Because FLOSS and Wikipedia have generatedthe majority of the peer production research to date, we focus on researchanalyzing those efforts. For each theoretical area, we briefly synthesize bothfoundational work and new directions and describe some of the challenges forfuture scholarship. Neither our themes nor our periodization are intended toencompass the complete literature on peer production. Instead, they reflectcore areas of research that speak most directly to the literature on collectiveintelligence and locate peer production within that broader phenomenon. Weconclude with a discussion of several issues that traverse our themes and impli-cations of peer production scholarship for research on collective intelligencemore broadly.

Although peer production is central to social scientific and legal researchon collective intelligence, not all examples of collective intelligence created inonline systems are peer production. First, (1) collective intelligence can in-volve centralized control over goal-setting and execution of tasks.

Peer production is the most significant organizational in-novation that has emerged from Internet-mediated social practice, among themost visible and important examples of collective intelligence, and a centraltheoretical frame used by social scientists and legal scholars of collective intel-ligence.

Following Benkler (2013), we define peer produc-tion as a form of open creation and sharing performed by groups online that:set and execute goals in a decentralized manner; harness a diverse range ofparticipant motivations, particularly non-monetary motivations; and sepa-rate governance and management relations from exclusive forms of propertyand relational contracts (i.e., projects are governed as open commons or com-mon property regimes and organizational governance utilizes combinationsof participatory, meritocratic and charismatic, rather than proprietary or con-

Consistent with this exam-ple, foundational social scientific research relevant to understanding collec-tive intelligence has focused on three central concerns: (1) explaining the or-ganization and governance of decentralized projects, (2) understanding themotivation of contributors in the absence of financial incentives or coerciveobligations, and (3) evaluating the quality of the products generated throughcollective intelligence systems.

Historically,researchers in diverse fields such as communication, sociology, law, and eco-nomics have argued that effective human systems organize people through acombination of hierarchical structures (e.g., bureaucracies), completely dis-tributed coordination mechanisms (e.g., markets), and social institutions ofvarious kinds (e.g., cultural norms). However, the rise of networked systemsand online platforms for collective intelligence has upended many of the as-sumptions and findings from this earlier research.

mporal features. We have then to consider how organizational participants are affected by situations containing temporal features, but also how these actors shape, by their behavior and beliefs, local context according to their needs.

To this extent, we have made tremendous advancements but we are still lacking reliable findings of the consistency and magnitude of the time effects at each level of an organization and on individuals. Perhaps, the last progresses that drawn upon the sructuration theory (Gomez, 2009; Kaplan & Orlikowski, 2013; Wanda J. Orlikowski & Yates, 2002; Reinecke & Ansari, 2015; Rowell, Gustafsson, & Clemente, 2016) has suffered the same faith of being judged as too notional and not providing enough guidance on how to conduct empirical studies based on this conception.

s a means for coordinating action among groups of users (e.g., Bardram, 2005, this volume)

The hierarchical structure of the Boer et al. adaptation of the Activity Theory model can help to reconcile the differences in granularity and the difficulties of supporting collaboration identified in our work; future activity-centered user interfaces might take advantage of the zoomable user interface paradigm or feature control over the level of detail (LOD) represented in the interface to more accurately reflect the depth at which a given user conceptualizes their own tasks or the tasks of their colleagues.

Activities also span place; that is, it is common for work to take place outside of the immediate office environment. However, current office technologies sometimes present a very different view of information across different physical and virtual settings.

The idea that activities may exist at different levels of granularity is not a new one. Boer, van Baalen & Kumar (2002) provide a model explaining how an activity at one level of analysis may be modeled as an action—a component of an activity—at another. This holds true for individual users, as in the example provided above, but is even more pronounced when a single activity is viewed from multiple participants’ perspectives.

Additionally, activities need to be represented in such a way that their contents can be shared, with the caveats that individual participants in an activity may have very different perceptions of the activity, they may bring different resources to play over the course of the activity, and, particularly for large activities in which many individual users participate, users themselves may come and go over the life of the activity.

Recognizing the mediating role of the digital work environment in enabling users to meaningfully collaborate is a critical step to ensuring the success of these systems.

Social identities have increasing difficulty in being construed in terms of stable social attributes in a highly mobile -both socially and geographically - society. They will have to rely on other, temporal dimensions, in what are becoming increasingly precari-ous, if not completely contingent, identities in constant need of redefi-nition. One's 'own', proper time situated in a momentous present which is extended on the societal level in order to accommodate the pressing overload of problems, choices and strategies, becomes a central value for the individual as well as a characteristic of the societal system (Nowotny, 1989a)

Major societal transformations are linked to information and communication technologies, giving rise to processes of growing global interdependence. They in turn generate the approxi-mation of coevalness, the illusion of simultaneity by being able to link instantly people and places around the globe. Many other processes are also accelerated. Speed and mobility are thus gaining in momentum, leading in turn to further speeding up processes that interlink the move-ment of people, information, ideas and goods.

ut it will also have to come to terms with confronting 'the Other' (Fabian, 1983), with 'the curious asymmetry' still prevailing as a result of advanced industrial societies receiving a mainly endogenous and synchronic analytic treatment, while 'developing' societies are often seen in exogenous, diachronic terms. Study of 'Time and the Other' presupposes, often implicitly, that the Other lives in another time, or at least on a different time-scale. And indeed, when looking at the integrative but also potentially divisive 'timing' facilitated by modern communication and information-processing technology, is it not correct to say that new divisions, on a temporal scale, are being created between those who have access to such devices and those who do not? Is not one part of humanity, despite globalization, in danger of being left behind, in a somewhat anachronistic age?

only structural functional theory, but all postfunctionalist 'successor' theories for their lack in taking up 'substantive' temporal issues, he was also pleading from the selective point of view of Third World countries for the exploration of theoretically possible alternatives or, to put it into other words, the delineation of what in the experience of western and non-western societies so far is universally valid and yet historically restric-ted. Such questions touch the very essence of the process of moderniz-ation. They evoke images of a closed past and an open or no longer so open future, of structures of collective memory as well as shifting collec-tive and individual identities of people who are increasingly drawn into the processes of world-wide integration and globalization. Anthropologi-cal accounts are extremely rich in different time reckoning modes and systems, in the pluritemporalism that prevailed in pre-industrialized societies. The theory of historical time - or times - both from a western and non-western point of view still has to be written. There exists already an impressive corpus of writings analysing the rise of the new dominant 'western' concept of time and especially its links with the process of industrialization. The temporal representations underlying the different disciplines in the social sciences allow not only for a reconceptualization of their division of intellectual labour, but also for a programmatic view forward towards a 'science of multiple times' (Grossin, 1989). However, any such endeavour has to come to terms also with non-western temporal experience.

Time' and time research is not ·an institutionalized subfield or subspeciality of any of the social sciences. By its very nature, it is recalcitrantly transdisciplinary and refuses to be placed under the intellectual monopoly of any discipline. Nor is time sufficiently recognized as forming an integral dimension of any of the more permanent structural domains of social life which have led to their institutionalization as research fields. Although research grants can be obtained for 'temporal topics', they are much more likely to be judged as relevant when they are presented as part of an established research field, such as studies of working time being considered a legit-imate part of studies of working life or industrial relations.

The standardization of local times into standard world time is one of the prime examples for the push towards standardization and integration also on the temporal scale (Zerubavel, 1982).

At present, information and communication technologies con-tinue to reshape temporal experience and collective time consciousness (Nowotny, 1989b)

Despite the apparent diversity of themes, certain common patterns can be discerned in empirical studies dealing with time. They bear the imprint of the ups and downs of research fashions as well as the waxing and waning of influences from neighbouring disciplines. But they all acknowledge 'time as a problem' in 'time-compact' societies (Lenntorp, 1978), imbued with the pressures of time that come from time being a scarce resource.

Studies of time in organizations have long since recognized the importance of 'events' as a complex admixture which shapes social life inside an organiz-ation and its relationship to the outside world. 'Sociological analyses', we are told, 'require a theory of time which recognizes that time is a socially constructed, organizing device by which one set, or trajectory of events is used as a point of reference for understanding, anticipating and attempting to control other sets of events. Time is in the events and events are defined by organizational members' (Clark, 1985:36).

The tension between action theory (or the theory of structuration) and sys-tems theory has not completely vanished, but at least the areas of dis-agreement have become clearer. The 'event' structure of time with its implicit legitimization through physics, but which is equally a central notion for historians (Grossin, 1989) holds a certain attraction for empiri-cal studies and for those who are interested in the definitional

The formation of time con epts and the making of time I measurements, i.e. the production of devices as well as their use and social function, become for him a problem of social knowledge and its formation. It is couched in the long-term perspective of evolution of human societies. Knowledge about time is not knowledge about an invariant part or object of nature. Time is not a quality inherent in things, nor invariant across human societies.

As can be seen by these and other theor~tical formulations, the prob-lem of time in social theory, while gradu~ ly coming to new terms with social action, does not lend itself easily 'to providing bridges for the agents behind human agency, the social actors, nor to those who do empirical research in order to understand the world from an actor's perspective.

As Bergmann (1981), and more recently, Ltischer (1989) and Adam (1990) and before them Joas (1980, 1989) have shown, a radical change in perspective away from time as 'flow' or time as embedded in the intentionality of the actor, can already be found in the social philosophy of time by G. H. Mead (Mead, 1936, 1932/1959, 1964). His is also a theory in which it is not the actor and his/her motives, interests or the means-ends scheme which dominates, but where action is interpreted as event -moreover, an event which is both temporal and social in nature.

It may well be, as Edmond Wright has pointed out (personal communi-cation) that by leaving sui generis time to the physicists, i.e. by leaving it out of social theory altogether, there is the risk of losing sight of the 'real' temporal continuum which serves as standard reference for all other forms of times. It also impedes coming to terms with 'time embedded' in natural objects and technical artifacts, as Hagerstrand (1974, 1975, 1988) repeatedly emphasized.

The fundamen-tal question for Giddens then becomes how social systems 'come to be stretched across time and space' (i.e. how they constitute their tempor-ality (Giddens, 1984).

quite different and much more radical approach is followed by Niklas Luhmann, who proposes to replace the subject/ action scheme by a time/action scheme, thus eliminating the actors alto-gether and replacing them with expectations and attributions.

To introduce time into present-day social theory means at its core to redefine its relation to social action and subsequently to human agency. It is there that the central questions arise, where differences begin to matter between action theory, structuration theory and system theory with regard to time.

he third strategy is the unen-cumbered embracing of pluritemporalism. With or without awareness that the concept of an absolute (Newtonian) physical time broke down irrevocably at the turn of this century and that a different kind of plurit-emporalism has also been spreading in the physical sciences (Prigogine and Stengers, 1988; Hawking, 1988; Adam, 1990), social theory is free to posit the existence of a plurality of times, including a plurality of social times. In most cases this amounts to a kind of 'theoretical agnosti-cism' with regard to physical time. Pluritemporalism allows for asserting the existence of social time next to physical ( or biological) time without going into differences of emergence, constitution or epistemological

Another strategy in dealing with sui generis time consists in juxtaposing clock time to the various forms of 'social time' and considers the latter as the more 'natural' ones, i.e. closer to subjective perceptions of time, or to the temporality that results from adaptations to seasons or other kinds of natural (biological, environmental) rhythm. This strategy, often couched also in terms of an opposition between 'linear' clock time and 'cyclical' time of natural and social rhythms devalues, or at least ques-tions, the temporality of formal organizations which rely heavily on clock time in fulfilling their coordinative and integrative and controlling functions (Young, 1988; Elchardus, 1988).

Searching to reconcile Darwinian evolutionary theory with Einsteinian relativity theory and, especially, its reconceptualization of simultaneity, Mead followed Whitehead's lead in locating the origins of all structuration of time in the notion of the 'event': without the interruption of the flow of time by events, no temporal experience would be possible (Joas, 1980, 1989)

Related to this encounter of the first kind, in which social theory meets the concept of time, is the question of the relationship between time in social systems with other forms of (physical, biological, 'natural') time or, as Elchardus calls it, 'sui generis time' (Elchardus, 1988).

By clarifying the concept of time as a conceptual symbol of evolving complex relationships between continua of changes of various kinds, Elias opens the way for grounding the concept of time again in social terms. The power of choosing the symbols, of selecting which continua are to be used, be it by priests or scientists, also beconies amenable to social analysis. The social matrix becomes ready once more to house the natural world or our conception of it in terms of its own, symbol-creating and continuously evolving capacity. The question of human agency is solved in Norbert Elias's case by referring to the process of human evolution through which men and women are enabled to devise symbols of increasing power of abstraction which are 'more adequate to reality'.

Unless one learns to perceive human societies, living in a world of symbols of their own making, as emerging and developing within the larger non-human universe, one is unable to attack one of the most crucial aspects of the problem of time. For Elias it consists, stated very briefly, in how to reconcile the highly abstract nature of the concept of time with the strong compulsion its social use as a regulatory device exerts upon us in daily life. His answer: time is not a thing, but a relationship. For him the word time is a symbol for a relationship which a group of beings endowed with the capacity for memory and synthesis establishes between two or more continua of changes, one of which is used by them as a frame of reference or standard of measurement for the other.

A definition of social time, like the one I attempted myself in the early 1970s, according to which the term social time 'refers to the experience of inter-subjective time created through social interaction, both on the behavioural and symbolic plane' now calls for a much more encompassing and dynamic definition, taking into account also the plurality of social times (Nowotny, 1975:326)

Martins draws a distinction between two criteria of temporalism and/or historicism. One he calls 'thematic tem-poralism', indicated by the degree to which temporal aspects of social life, diachronicity, etc., are taken seriously as themes for reflection of meta theoretical inquiry. The other criterion is the degree or level of 'substantive temporalism', the degree to which becoming, process or diachrony are viewed as ontological grounds for socio-cultural life or as methodologically prior to structural synchronic analysis or explanations.

There is also a widespread acknowledgement, especially in evidence in the empirical literature, of what I will call 'pluritemporalism'. This is an acknowledgement of the existence of a plurality of different modes of social time(s) which may exist side by side, and yet are to be distinguished from the time of physics or that of biology.

The demise of structural-functionalism, he argues, has not brought about a substantial increment in the degree of temporalism and historicism in the theoretical constructs of general sociology, even though this was one of the major goals announced by the critics of functionalism, paramount to a meta-theoretical criterion of what an 'adequate' theory should con-sist of.

The question is, rather, why the repeated complaint about the neglect of time in social theory or in the social sciences in general?

Sorokin and Merton in 1937, entitled 'Social Time: A Methodological and Functional Analysis' that some of the Durkheimian ideas were taken up again. This paper identified social time as qualitatively heterogeneous (e.g. holidays and market days), not quantitatively homogeneous as astronomical or physical time has it. Social time was seen as being divided into intervals that derive from collective social activities rather than being uniformly flowing. Local time systems, it was argued, function mainly in order to assure the coordination and synchronization of local activities which eventually become extended and integrated, thereby necessitating common time systems. The Durkheimian claim of the category of time being rooted in social activities, of time being socially constituted by virtue of the 'rhythm of social life' itself, buttressed by the analysis of the social functions it served, was a tacit rebuttal of Kant's a priori intuitions of time, space and causality.

The claim to the existence of a concept of 'social time', distinct from other forms of time, was thus made early in the history of social thought. It continues to focus upon the claims of the peculiar nature of the 'social constitution' or the 'social construction' of time. These claims evidently put the category of 'social time' into the wider realm of 'symbolic time', a cultural phenomenon, the constitution of which has remained the object of inquiry of more disciplines than sociology alone, but which separates it from time in nature, embedded in things and artifacts.

In the then undeveloped sociology of knowledge, Durkheim held as the most general conclusion that it is the rhythm of social life which is the basis of the category of time itself (Durkheim, 1912:7). These obser-vations opened up important questions about the social origins and func-tions of the category of time and how social time can be distinguished and is distinct from astronomical time.

“If you’re not on MySpace, you don’t exist.”

identity why do teens seem strange online?292privacy why do youth share so publicly?543addiction what makes teens obsessed with social media?774danger are sexual predators lurking everywhere?1005bullying is social media amplifying meanness and cruelty?1286inequality can social media resolve social divisions?1537literacy are today’s youth digital natives?1768searching for a public of their own199

Sorokin and Merton (1937) may be said to have provided the 'definitive' classic statement on the distinction between social and natural time. They associate the physical time of diurnal and seasonal cycles with clock time and define this time as 'purely quantitative, shorn of qualitative variation' (p. 621). 'All time systems', Sorokin and Merton suggest further, 'may be reduced to the need of providing means for synchronising and co-ordinating the activities and observations of the constituents of groups' (p. 627).

I had been a victim of something the sociologists Alice Marwick and danah boyd call context collapse, where people create online culture meant for one in-group, but exposed to any number of out-groups without its original context by social-media platforms, where it can be recontextualized easily and accidentally.

Ten years ago, if I knew someone primarily through online means, you could guarantee they had their own domain name. It was just before the big explosion in social media use which meant that if you wanted a space online, you had to create it. This provided a barrier to entry in terms of the digital literacy skills required to register a domain, set up the necessary software and, of course, design, build and upload a website. The upside was that your digital identity was yours.

Brown and Eisenhardt studied change and project management in com­puter firms and found that firms with less successful project portfolios demon­strated very low amounts of communication across projects. This was part of the context in which projects were planned, divided into small tasks, and then executed in a “structured sequence of steps” (1997, p. 14). A structured sequence is, of course, a monochronic strategy, and the low amount of communication is consistent with the proposition that monochronic strategies generate less awareness of other activities and tasks. One of the managers in their study re­marked, “Most people only look at their part” (p. 14); another, “The work of everyone else doesn’t really affect my work” (p. 14). These responses contrasted with the pattern of work in the companies that managed their portfolios of projects more successfully, which Brown and Eisenhardt characterized as “it­erative” (p. 14). Iterative (repetitive) patterns are suggestive of the back and forth flow of polychronic strategies

in a more polychronic culture, people would stand closer to each other while talking. So time and space are related in the social as well as the physical world.

Then I used Gephi, another free data analysis tool, to visualize the data as an entity-relationship graph. The coloured circles—called Nodes—represent Twitter accounts, and the intersecting lines—known as Edges—refer to Follow/Follower connections between accounts. The accounts are grouped into colour-coded community clusters based on the Modularity algorithm, which detects tightly interconnected groups. The size of each node is based on the number of connections that account has with others in the network.

Using the open-source NodeXL tool, I collected and imported a complete list of accounts tweeting that exact phrase into a spreadsheet. From that list, I also gathered and imported an extended community of Twitter users, comprised of the friends and followers of each account. It was going to be an interesting test: if the slurs against Nemtsov were just a minor case of rumour-spreading, they probably wouldn't be coming from more than a few dozen users.

The New Yorker’s Sasha Frere-Jones called Twitter a “self-cleaning oven,” suggesting that false information could be flagged and self-corrected almost immediately. We no longer had to wait 24 hours for a newspaper to issue a correction.

Dissemination MechanismsFinally, we need to think about how this content is being disseminated. Some of it is being shared unwittingly by people on social media, clicking retweet without checking. Some of it is being amplified by journalists who are now under more pressure than ever to try and make sense and accurately report information emerging on the social web in real time. Some of it is being pushed out by loosely connected groups who are deliberately attempting to influence public opinion, and some of it is being disseminated as part of sophisticated disinformation campaigns, through bot networks and troll factories.

Bronislaw Malinowski addressed the functions of time as fol­lows: “A system of reckoning time is a practical, as well as a sentimental, ne­cessity in every culture, however simple. Members of every human group have the need of coordinating various activities, of fixing dates for the future, of placing reminiscences in the past, of gauging the length of bygone periods and of those to come” (1990, p. 203). Sixty-three years later Barbara Adam would state it thus: “As ordering principle, social tool for co-ordination, orientation, and regulation, as a symbol for the conceptual organisation of natural and so­cial events, social scientists view time as constituted by social activity” (1990, p. 42).

Time is a social construction, or more properly, times are socially constructed, which means the concepts and values we hold about various times are the prod­ucts of human interaction (Lauer 1981, p. 44). These social products and beliefs are generated in groups large and small, but it is not that simple. For contrary to Emile Durkheim’s assertion, not everyone in the group holds a common time, a time “such as it is objectively thought of by everybody in a single civilization” (1915, p. 10). This is so because in the perpetual structuration of social life (Gid­dens 1984) individuals bring their own interpretations to received social knowl­edge, and these interpretations add variance to the beliefs, perceptions, and val­ues.

A third paradox is only hinted at by Vmho, when he suggests that conflict is to be expected between democracy and dromocracy, the politics that take account of time and the speed of movement across space.20 It concerns the sociopolitical and socioeconomic relations associated with advances in transport speed, which affect dif­ferent indivi�uals, groups and classes of society in uneven ways.

In the light of this evidence, which is fully supported by transport research, 17 Virilio formulated the �romological law, which states that increase in speed mcreases the potential for gridlock.

The task for social theory, therefore, is to render the invisible visible, show relations and intercon­nections, begin tbe process of questioning the unquestioned. Before we can identify some of these economic relations of temporal inequity, however, we first need to understand in what way the sin of usury was a barrier to the develop­ment of economic life as we know it today in industrial societies.

Leshed and Sengers’s research reminds us that calendars are not just tools for the management of time, but are also sites of identity work where people can project to themselves and others the density of their days and apparent ‘success’ at doing it all[26]. These seemingly innocuous artifacts can thus perpetuate deeper normative logics a

. When creating tools for schedulingandcoordination, it is crucial to provide ways for people to take into account not just the multiplicity of (potentially dissonant) rhythms [22, 46], but also the differential affective experiencesof time rendered by such rhythms.