150 Matching Annotations
  1. Jul 2024
    1. https://en.wikipedia.org/wiki/Matthew_effect

      The Matthew effect of accumulated advantage, sometimes called the Matthew principle, is the tendency of individuals to accrue social or economic success in proportion to their initial level of popularity, friends, and wealth. It is sometimes summarized by the adage or platitude "the rich get richer and the poor get poorer". The term was coined by sociologists Robert K. Merton and Harriet Zuckerman in 1968 and takes its name from the Parable of the Talents in the biblical Gospel of Matthew.

      related somehow to the [[Lindy effect]]?

  2. Jan 2024
    1. The Evaporative Cooling Effect describes the phenomenon that high value contributors leave a community because they cannot gain something from it, which leads to the decrease of the quality of the community. Since the people most likely to join a community are those whose quality is below the average quality of the community, these newcomers are very likely to harm the quality of the community. With the expansion of community, it is very hard to maintain the quality of the community.

      via ref to Xianhang Zhang in Social Software Sundays #2 – The Evaporative Cooling Effect « Bumblebee Labs Blog [archived] who saw it

      via [[Eliezer Yudkowsky]] in Evaporative Cooling of Group Beliefs

  3. Aug 2023
    1. Health care is an area that will likely see many innovations. There are already multiple research prototypes underway looking at monitoring of one’s physical and mental health. Some of my colleagues (and myself as well) are also looking at social behaviors, and how those behaviors not only impact one’s health but also how innovations spread through one’s social network.
      • for: quote, quote - Jason Hong, quote - health apps, health care app, idea spread through social network, mental health app, physical health app, transform app
      • quote
      • paraphrase
        • Health care is an area that will likely see many innovations. -There are already multiple research prototypes underway looking at monitoring of one’s
          • physical and
          • mental health.
        • Some of my colleagues (and myself as well) are also looking at
          • social behaviors, and how those behaviors
            • not only impact one’s health but also
            • how innovations spread through one’s social network.
  4. Jul 2023
  5. Feb 2023
  6. Dec 2022
    1. We repeat this procedure 10,000 times. The value of 10,000 was selected because 9604 is the minimum size of samples required to estimate an error of 1 % with 95 % confidence [this is according to a conservative method; other methods also require <10,000 samples size (Newcombe 1998)]
    1. In this work, we develop the “Multi-Agent, Multi-Attitude” (MAMA) model which incorporates several key factors of attitude diffusion: (1) multiple, interacting attitudes; (2) social influence between individuals; and (3) media influence. All three components have strong support from the social science community.

      several key factors of attitude diffusion: 1. multiple, interacting attitudes 2. social influence between individuals 3. media influence

  7. Aug 2022
  8. Apr 2022
    1. 3. Who are you annotating with? Learning usually needs a certain degree of protection, a safe space. Groups can provide that, but public space often less so. In Hypothes.is who are you annotating with? Everybody? Specific groups of learners? Just yourself and one or two others? All of that, depending on the text you’re annotating? How granular is your control over the sharing with groups, so that you can choose your level of learning safety?

      This is a great question and I ask it frequently with many different answers.

      I've not seen specific numbers, but I suspect that the majority of Hypothes.is users are annotating in small private groups/classes using their learning management system (LMS) integrations through their university. As a result, using it and hoping for a big social experience is going to be discouraging for most.

      Of course this doesn't mean that no one is out there. After all, here you are following my RSS feed of annotations and asking these questions!

      I'd say that 95+% or more of my annotations are ultimately for my own learning and ends. If others stumble upon them and find them interesting, then great! But I'm not really here for them.

      As more people have begun using Hypothes.is over the past few years I have slowly but surely run into people hiding in the margins of texts and quietly interacted with them and begun to know some of them. Often they're also on Twitter or have their own websites too which only adds to the social glue. It has been one of the slowest social media experiences I've ever had (even in comparison to old school blogging where discovery is much higher in general use). There has been a small uptick (anecdotally) in Hypothes.is use by some in the note taking application space (Obsidian, Roam Research, Logseq, etc.), so I've seen some of them from time to time.

      I can only think of one time in the last five or so years in which I happened to be "in a text" and a total stranger was coincidentally reading and annotating at the same time. There have been a few times I've specifically been in a shared text with a small group annotating simultaneously. Other than this it's all been asynchronous experiences.

      There are a few people working at some of the social side of Hypothes.is if you're searching for it, though even their Hypothes.is presences may seem as sparse as your own at present @tonz.

      Some examples:

      @peterhagen Has built an alternate interface for the main Hypothes.is feed that adds some additional discovery dimensions you might find interesting. It highlights some frequent annotators and provide a more visual feed of what's happening on the public Hypothes.is timeline as well as data from HackerNews.

      @flancian maintains anagora.org, which is like a planet of wikis and related applications, where he keeps a list of annotations on Hypothes.is by members of the collective at https://anagora.org/latest

      @tomcritchlow has experimented with using Hypothes.is as a "traditional" comments section on his personal website.

      @remikalir has a nice little tool https://crowdlaaers.org/ for looking at documents with lots of annotations.

      Right now, I'm also in an Obsidian-based book club run by Dan Allosso in which some of us are actively annotating the two books using Hypothes.is and dovetailing some of this with activity in a shared Obsidian vault. see: https://boffosocko.com/2022/03/24/55803196/. While there is a small private group for our annotations a few of us are still annotating the books in public. Perhaps if I had a group of people who were heavily interested in keeping a group going on a regular basis, I might find the value in it, but until then public is better and I'm more likely to come across and see more of what's happening out there.

      I've got a collection of odd Hypothes.is related quirks, off label use cases, and experiments: https://boffosocko.com/tag/hypothes.is/ including a list of those I frequently follow: https://boffosocko.com/about/following/#Hypothesis%20Feeds

      Like good annotations and notes, you've got to put some work into finding the social portion what's happening in this fun little space. My best recommendation to find your "tribe" is to do some targeted tag searches in their search box to see who's annotating things in which you're interested.

    1. One of the most effective ways of enhancing memories is to provide them with a link to your personal life.

      Personalizing ideas using existing memories is a method of brining new knowledge into one's own personal context and making them easier to remember.

      link this to: - the pedagogical idea of context shifting as a means of learning - cards about reframing ideas into one's own words when taking notes

      There is a solid group of cards around these areas of learning.


      Random thought: Personal learning networks put one into a regular milieu of people who are talking and thinking about topics of interest to the learner. Regular discussions with these people helps one's associative memory by tying the ideas into this context of people with relation to the same topic. Humans are exceedingly good at knowing and responding to social relationships and within a personal learning network, these ties help to create context on an interpersonal level, but also provide scaffolding for the ideas and learning that one hopes to do. These features will tend to reinforce each other over time.

      On the flip side of the coin there is anecdotal evidence of friends taking courses together because of their personal relationships rather than their interest in the particular topics.

  9. Feb 2022
  10. Jan 2022
  11. Dec 2021
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  14. Sep 2021
  15. Aug 2021
  16. Jul 2021
  17. May 2021
  18. Apr 2021
  19. Mar 2021
  20. Feb 2021
    1. Economists call this a "network effect": the more people there are on Twitter, the more reason there is to be on Twitter and the harder it is to leave. But technologists have another name for this: "lock in." The more you pour into Twitter, the more it costs you to leave. Economists have a name for that cost: the "switching cost."
  21. Oct 2020
    1. So that’s already a huge advantage over other platforms due the basic design. And in my opinion it’s got advantages over the other extreme, too, a pure peer-to-peer design, where everyone would have to fend for themselves, without the pooled resources.

      Definitely something the IndieWeb may have to solve for.

    2. Mastodon deliberately does not support arbitrary search. If someone wants their message to be discovered, they can use a hashtag, which can be browsed. What does arbitrary search accomplish? People and brands search for their own name to self-insert into conversations they were not invited to. What you can do, however, is search messages you posted, received or favourited. That way you can find that one message on the tip of your tongue.
    1. First, I will focus in these larger groups because reviews that transcend the boundary between the social and natural sciences are rare, but I believe them to be valuable. One such review is Borgatti et al. (2009), which compares the network science of natural and social sciences arriving at a similar conclusion to the one I arrived.
  22. Sep 2020
  23. Aug 2020
  24. Jul 2020
  25. Jun 2020