keystroke biometrics, ID capture, and facial analysis
I feel like I'm seeing various responses to what data is actually captured. To me, it doesn't seem like they are consistent in their responses about the types of data collected.
keystroke biometrics, ID capture, and facial analysis
I feel like I'm seeing various responses to what data is actually captured. To me, it doesn't seem like they are consistent in their responses about the types of data collected.
Maybe your dbt models depend on source data tables that are populated by Stitch ingest, or by heavy transform jobs running in Spark. Maybe the tables your models build are depended on by analysts building reports in Mode, or ML engineers running experiments using Jupyter notebooks. Whether you’re a full-stack practitioner or a specialized platform team, you’ve probably felt the pain of trying to track dependencies across technologies and concerns. You need an orchestrator.Dagster lets you embed dbt into a wider orchestration graph.
It can be common for [[data models]] to rely on other sources - where something like [[Dagster]] fits in - is allowing your dbt fit into a wider [[orchestration graph]]
We love dbt because of the values it embodies. Individual transformations are SQL SELECT statements, without side effects. Transformations are explicitly connected into a graph. And support for testing is first-class. dbt is hugely enabling for an important class of users, adapting software engineering principles to a slightly different domain with great ergonomics. For users who already speak SQL, dbt’s tooling is unparalleled.
when using [[dbt]] the [[transformations]] are [[SQL statements]] - already something that our team knows
What is dbt?dbt was created by Fishtown Analytics to enable data analysts to build well-defined data transformations in an intuitive, testable, and versioned environment.Users build transformations (called models) defined in templated SQL. Models defined in dbt can refer to other models, forming a dependency graph between the transformations (and the tables or views they produce). Models are self-documenting, easy to test, and easy to run. And the dbt tooling can use the graph defined by models’ dependencies to determine the ancestors and descendants of any individual model, so it’s easy to know what to recompute when something changes.
one of the [[benefits of [[dbt]]]] is that the [[data transformations]] or [[data models]] can refer to other models, and help show the [[dependency graph]] between transformatios
self-service data platform
The attribution data modelIn reality, it’s impossible to know exactly why someone converted to being a customer. The best thing that we can do as analysts, is provide a pretty good guess. In order to do that, we’re going to use an approach called positional attribution. This means, essentially, that we’re going to weight the importance of various touches (customer interactions with a brand) based on their position (the order they occur in within the customer’s lifetime).To do this, we’re going to build a table that represents every “touch” that someone had before becoming a customer, and the channel that led to that touch.
One of the goals of an [[attribution data model]] is to understand why someone [[converted]] to being a customer. This is impossible to do accurately, but this is where analysis comes in.
There are some [[approaches to attribution]], one of those is [[positional attribution]]
[[positional attribution]] is that we are weighting the importance of touch points - or customer interactions, based on their position within the customer lifetime.
Marketers have been told that attribution is a data problem -- “Just get the data and you can have full knowledge of what’s working!” -- when really it’s a data modeling problem. The logic of your attribution model, what the data represents about your business, is as important as the data volume. And the logic is going to change based on your business. That’s why so many attribution products come up short.
attribution isn't a data problem, it's a data modeling problem]] - it's not just the data, but what the data represents about your business.
I increasingly don’t care for the world of centralized software. Software interacts with my data, on my computers. Its about time my software reflected that relationship. I want my laptop and my phone to share my files over my wifi. Not by uploading all my data to servers in another country. Especially if those servers are financed by advertisers bidding for my eyeballs.
This is until you realize you're probably using at least ten different services, and they all have different purposes, with various kinds of data, endpoints and restrictions. Even if you have the capacity and are willing to do it, it's still damn hard.
Hopefully we can agree that the current situation isn't so great. But I am a software engineer. And chances that if you're reading it, you're very likely a programmer as well. Surely we can deal with that and implement, right? Kind of, but it's really hard to retrieve data created by you.
Online Research Tools and Techniques. (2020, September 16). https://www.youtube.com/watch?v=wGWqBtDkOFs
ORWG Virtual Meeting 08/09/2020 https://www.youtube.com/playlist?list=PLOA0aRJ90NxvXtMt5Si5ukmR9LYfvDueB (n.d.)
Brous, P., & Janssen, M. (2020). Trusted Decision-Making: Data Governance for Creating Trust in Data Science Decision Outcomes. Administrative Sciences, 10(4), 81. https://doi.org/10.3390/admsci10040081
Note: it does not mutate the object, but returns a new object.
Cates, J. (2020). Risk for In-Hospital Complications Associated with COVID-19 and Influenza—Veterans Health Administration, United States, October 1, 2018–May 31, 2020. MMWR. Morbidity and Mortality Weekly Report, 69. https://doi.org/10.15585/mmwr.mm6942e3
Elmas, T., Overdorf, R., Akgül, Ö. F., & Aberer, K. (2020). Misleading Repurposing on Twitter. ArXiv:2010.10600 [Cs]. http://arxiv.org/abs/2010.10600
Epidemiologische Abklärung Covid 19. (n.d.). AGES - Österreichische Agentur Für Gesundheit Und Ernährungssicherheit. Retrieved October 28, 2020, from https://www.ages.at/themen/krankheitserreger/coronavirus/epidemiologische-abklaerung-covid-19/
(d) All calculations shown in this appendix shall be implemented on a site-level basis. Site level concentration data shall be processed as follows: (1) The default dataset for PM2.5 mass concentrations for a site shall consist of the measured concentrations recorded from the designated primary monitor(s). All daily values produced by the primary monitor are considered part of the site record; this includes all creditable samples and all extra samples. (2) Data for the primary monitors shall be augmented as much as possible with data from collocated monitors. If a valid daily value is not produced by the primary monitor for a particular day (scheduled or otherwise), but a value is available from a collocated monitor, then that collocated value shall be considered part of the combined site data record. If more than one collocated daily value is available, the average of those valid collocated values shall be used as the daily value. The data record resulting from this procedure is referred to as the “combined site data record.”
Outbreak.info. (n.d.). Outbreak.Info. Retrieved October 25, 2020, from https://outbreak.info/
Woolf, S. H., Chapman, D. A., Sabo, R. T., Weinberger, D. M., Hill, L., & Taylor, D. D. H. (2020). Excess Deaths From COVID-19 and Other Causes, March-July 2020. JAMA, 324(15), 1562. https://doi.org/10.1001/jama.2020.19545
Leatherby, L. (2020, October 15). U.S. Virus Cases Climb Toward a Third Peak. The New York Times. https://www.nytimes.com/interactive/2020/10/15/us/coronavirus-cases-us-surge.html
Institutions that were primarily online before the pandemic are also doing well. At colleges where more than 90 percent of students took courses solely online pre-pandemic, enrollments are growing for both undergraduate (6.8 percent) and graduate students (7.2 percent).
If you define a variable outside of your form, you can then set the value of that variable to the handleSubmit function that 🏁 React Final Form gives you, and then you can call that function from outside of the form.
AI and control of Covid-19 coronavirus. (n.d.). Artificial Intelligence. Retrieved October 15, 2020, from https://www.coe.int/en/web/artificial-intelligence/ai-and-control-of-covid-19-coronavirus
We could freeze the objects in the model but don't for efficiency. (The benefits of an immutable-equivalent data structure will be documented in vtree or blog post at some point)
first sighting: "immutable-equivalent data"
A VTree is designed to be equivalent to an immutable data structure. While it's not actually immutable, you can reuse the nodes in multiple places and the functions we have exposed that take VTrees as arguments never mutate the trees.
We don't know if the passed in props is a user created object that can be mutated so we must always clone it once.
Howard, M. C. (2021). Gender, face mask perceptions, and face mask wearing: Are men being dangerous during the COVID-19 pandemic? Personality and Individual Differences, 170, 110417. https://doi.org/10.1016/j.paid.2020.110417
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(((Howard Forman))) on Twitter. (n.d.). Twitter. Retrieved October 12, 2020, from https://twitter.com/thehowie/status/1315418282590121984
r/BehSciResearch—Review on combatting the COVID misinformation flood. (n.d.). Reddit. Retrieved October 12, 2020, from https://www.reddit.com/r/BehSciResearch/comments/j9mrlp/review_on_combatting_the_covid_misinformation/
Gallagher, J. (2020, October 9). Covid cases increase rapidly as next steps planned. BBC News. https://www.bbc.com/news/health-54477618
Dominique Heinke on Twitter. (n.d.). Twitter. Retrieved October 12, 2020, from https://twitter.com/Epi_D_Nique/status/1314753256556552192
Non-Covid infectious disease cases down in England, data suggests. (2020, October 9). The Guardian. http://www.theguardian.com/science/2020/oct/09/non-covid-infectious-disease-cases-down-in-england-data-suggests
Trias-Llimós, S., Alustiza, A., Prats, C., Tobias, A., & Riffe, T. (2020). The need for detailed COVID-19 data in Spain. The Lancet Public Health, 0(0). https://doi.org/10.1016/S2468-2667(20)30234-6
Dr Duncan Robertson on Twitter. (n.d.). Twitter. Retrieved October 12, 2020, from https://twitter.com/Dr_D_Robertson/status/1314544108547997703
COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved October 11, 2020, from https://covid-19.iza.org/publications/dp13620/
COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved October 11, 2020, from https://covid-19.iza.org/publications/dp13640/
New tool for the early detection of public health threats from Twitter data: Epitweetr. (2020, October 1). European Centre for Disease Prevention and Control. https://www.ecdc.europa.eu/en/news-events/new-tool-early-detection-public-health-threats-twitter-data-epitweetr
Davis, N., & Boseley, S. (2020, October 9). Coronavirus: At least three-quarters of people in UK fail to self-isolate. The Guardian. https://www.theguardian.com/world/2020/oct/09/covid-in-england-latest-figures-suggest
Legislation to stem the tide of Big Tech companies' abuses, and laws—such as a national consumer privacy bill, an interoperability bill, or a bill making firms liable for data-breaches—would go a long way toward improving the lives of the Internet users held hostage inside the companies' walled gardens. But far more important than fixing Big Tech is fixing the Internet: restoring the kind of dynamism that made tech firms responsive to their users for fear of losing them, restoring the dynamic that let tinkerers, co-ops, and nonprofits give every person the power of technological self-determination.
(Roose, who has since deleted his tweet as part of a routine purge of tweets older than 30 days, told me it was intended simply as an observation, not a full analysis of the trends.)
Another example of someone regularly deleting their tweets at regular intervals. I've seem a few examples of this in academia.
More conspicuously, since Trump’s election, the RNC — at his campaign’s direction — has excluded critical “voter scores” on the president from the analytics it routinely provides to GOP candidates and committees nationwide, with the aim of electing down-ballot Republicans. Republican consultants say the Trump information is being withheld for two reasons: to discourage candidates from distancing themselves from the president, and to avoid embarrassing him with poor results that might leak. But they say its concealment harms other Republicans, forcing them to campaign without it or pay to get the information elsewhere.
A statistician is the exact same thing as a data scientist or machine learning researcher with the differences that there are qualifications needed to be a statistician, and that we are snarkier.
you can then use “Sign In with Google” to access the publisher’s products, but Google does the billing, keeps your payment method secure, and makes it easy for you to manage your subscriptions all in one place.
I immediately wonder who owns my related subscription data? Is the publisher only seeing me as a lumped Google proxy or do they get may name, email address, credit card information, and other details?
How will publishers be able (or not) to contact me? What effect will this have on potential customer retention?
Methodology To determine the link between heat and income in U.S. cities, NPR used NASA satellite imagery and U.S. Census American Community Survey data. An open-source computer program developed by NPR downloaded median household income data for census tracts in the 100 most populated American cities, as well as geographic boundaries for census tracts. NPR combined these data with TIGER/Line shapefiles of the cities.
This is an excellent example of data journalism.
Solid’s State primitive is arguably its most powerful and distinctive one. Through the use of proxies and explicit setters it gives the control of an immutable interface and the performance of a mutable one
In contrast, data is just mutated in Vue.
We have to be careful not to mutate state so when we have some complex state like an object or an array we have to use some ugly tricks like in the setTodoCompleted function above.
Shauna Brail on Twitter. (n.d.). Twitter. Retrieved October 9, 2020, from https://twitter.com/shaunabrail/status/1313818873163067392
Stix, Y. Z., Gary. (n.d.). COVID-19 Is Now the Third Leading Cause of Death in the U.S. Scientific American. Retrieved October 9, 2020, from https://www.scientificamerican.com/article/covid-19-is-now-the-third-leading-cause-of-death-in-the-u-s1/
Note that interacting with these <input> elements will mutate the array. If you prefer to work with immutable data, you should avoid these bindings and use event handlers instead.
use-methods is built on immer, which allows you to write your methods in an imperative, mutating style, even though the actual state managed behind the scenes is immutable.
NIH VideoCast—Joseph Leiter NLM/MLA Lectureship: Digital Epidemiology and the COVID-19 Pandemic. (n.d.). Retrieved 6 October 2020, from https://videocast.nih.gov/watch=38269
Fionna O’Leary, 🕯 on Twitter. (n.d.). Twitter. Retrieved October 6, 2020, from https://twitter.com/fascinatorfun/status/1312855480956575744
IZA – Institute of Labor Economics. ‘COVID-19 and the Labor Market’. Accessed 6 October 2020. https://covid-19.iza.org/publications/dp13737/.
IZA – Institute of Labor Economics. ‘COVID-19 and the Labor Market’. Accessed 6 October 2020. https://covid-19.iza.org/publications/dp13690/.
1.1. Monitors For the purposes of AQS, a monitor does not refer to a specific piece of equipment. Instead, it reflects that a given pollutant (or other parameter) is being measured at a given site. Identified by: The site (state + county + site number) where the monitor is located AND The pollutant code AND POC – Parameter Occurrence Code. Used to uniquely identify a monitor if there is more than one device measuring the same pollutant at the same site. For example monitor IDs are usually written in the following way: SS-CCC-NNNN-PPPPP-Q where SS is the State FIPS code, CCC is the County FIPS code, and NNNN is the Site Number within the county (leading zeroes are always included for these fields), PPPPP is the AQS 5-digit parameter code, and Q is the POC. For example: 01-089-0014-44201-2 is Alabama, Madison County, Site Number 14, ozone monitor, POC 2.
How monitors (specific measures of specific criteria) are identified in AQS data.
2019nCOV. (n.d.). MOBS Lab. Retrieved October 2, 2020, from https://www.mobs-lab.org/2019ncov.html
Karatayev, Vadim A., Madhur Anand, and Chris T. Bauch. ‘Local Lockdowns Outperform Global Lockdown on the Far Side of the COVID-19 Epidemic Curve’. Proceedings of the National Academy of Sciences 117, no. 39 (29 September 2020): 24575–80. https://doi.org/10.1073/pnas.2014385117.
2020 Conference on Computational Sociology | IRiSS. (n.d.). Retrieved 30 September 2020, from https://iriss.stanford.edu/css/conferences/2020-conference-computational-sociology
Computational Social Science to Address the (Post) COVID-19 Reality. (2020, June 27). https://www.youtube.com/watch?v=7d-Dq0e1JJ0&list=PL9UNgBC7ODr6eZkwB6W0QSzpDs46E8WPN&index=4
Thacker, P. D. (2020). A few tiny steps towards transparency: How the Sunshine Act shone light on industry’s influence in medicine. BMJ, 370. https://doi.org/10.1136/bmj.m3229
Harvard’s Chetty Finds Economic Carnage in Wealthiest ZIP Codes. (2020, September 24). Bloomberg.Com. https://www.bloomberg.com/news/features/2020-09-24/harvard-economist-raj-chetty-creates-god-s-eye-view-of-pandemic-damage
Knawy, B. A., Adil, M., Crooks, G., Rhee, K., Bates, D., Jokhdar, H., Klag, M., Lee, U., Mokdad, A. H., Schaper, L., Hazme, R. A., Khathaami, A. M. A., & Abduljawad, J. (2020). The Riyadh Declaration: The role of digital health in fighting pandemics. The Lancet, 0(0). https://doi.org/10.1016/S0140-6736(20)31978-4
Tim spector on Twitter. (n.d.). Twitter. Retrieved September 25, 2020, from https://twitter.com/timspector/status/1308873677807792129
Online Research: From Funding to Data Collection. (n.d.). Association for Psychological Science - APS. Retrieved September 25, 2020, from https://www.psychologicalscience.org/news/online-research.html
"The Data Visualisation Catalogue is a project developed by Severino Ribecca to create a library of different information visualisation types." I like the explanations of when one might use a particular type of data visualization to highlight - or obscure! - what the data is saying.
Ruktanonchai, N. W., Floyd, J. R., Lai, S., Ruktanonchai, C. W., Sadilek, A., Rente-Lourenco, P., Ben, X., Carioli, A., Gwinn, J., Steele, J. E., Prosper, O., Schneider, A., Oplinger, A., Eastham, P., & Tatem, A. J. (2020). Assessing the impact of coordinated COVID-19 exit strategies across Europe. Science, 369(6510), 1465–1470. https://doi.org/10.1126/science.abc5096
Nagaraj, A., Shears, E., & Vaan, M. de. (2020). Improving data access democratizes and diversifies science. Proceedings of the National Academy of Sciences, 117(38), 23490–23498. https://doi.org/10.1073/pnas.2001682117
The RDF model encodes data in the form ofsubject,predicate,objecttriples. The subjectand object of a triple are both URIs that each identify a resource, or a URI and a stringliteral respectively. The predicate specifies how the subject and object are related, and isalso represented by a URI.
Basic description of Resource Description Framework
Facebook ignored or was slow to act on evidence that fake accounts on its platform have been undermining elections and political affairs around the world, according to an explosive memo sent by a recently fired Facebook employee and obtained by BuzzFeed News.The 6,600-word memo, written by former Facebook data scientist Sophie Zhang, is filled with concrete examples of heads of government and political parties in Azerbaijan and Honduras using fake accounts or misrepresenting themselves to sway public opinion. In countries including India, Ukraine, Spain, Brazil, Bolivia, and Ecuador, she found evidence of coordinated campaigns of varying sizes to boost or hinder political candidates or outcomes, though she did not always conclude who was behind them.
(((Howard Forman))) on Twitter. (n.d.). Twitter. Retrieved September 23, 2020, from https://twitter.com/thehowie/status/1308107599682756609
Graham Cooke on Twitter. (n.d.). Twitter. Retrieved September 23, 2020, from https://twitter.com/grahamscooke/status/1308132497822281728
Obradovich, N., Özak, Ö., Martín, I., Ortuño-Ortín, I., Awad, E., Cebrián, M., Cuevas, R., Desmet, K., Rahwan, I., & Cuevas, Á. (2020). Expanding the measurement of culture with a sample of two billion humans [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/qkf42
Romanini, Daniele, Sune Lehmann, and Mikko Kivelä. ‘Privacy and Uniqueness of Neighborhoods in Social Networks’. ArXiv:2009.09973 [Physics], 21 September 2020. http://arxiv.org/abs/2009.09973.
Provides state management for tree-like components. Handles building a collection of items from props, item expanded state, and manages multiple selection state.
Adam Kucharski on Twitter. (n.d.). Twitter. Retrieved September 22, 2020, from https://twitter.com/AdamJKucharski/status/1307231588732764161
Friston, K., Costello, A., & Pillay, D. (2020). Dark matter, second waves and epidemiological modelling. MedRxiv, 2020.09.01.20185876. https://doi.org/10.1101/2020.09.01.20185876
Carl T. Bergstrom on Twitter. (n.d.). Twitter. Retrieved September 22, 2020, from https://twitter.com/CT_Bergstrom/status/1306995362368954369
Kyle Griffin on Twitter. (n.d.). Twitter. Retrieved September 22, 2020, from https://twitter.com/kylegriffin1/status/1307343837891833861
Holman, E. A., Thompson, R. R., Garfin, D. R., & Silver, R. C. (2020). The unfolding COVID-19 pandemic: A probability-based, nationally representative study of mental health in the U.S. Science Advances, eabd5390. https://doi.org/10.1126/sciadv.abd5390
Nic Fildes in London and Javier Espinoza in Brussels April 8 2020 Jump to comments section Print this page Be the first to know about every new Coronavirus story Get instant email alerts When the World Health Organization launched a 2007 initiative to eliminate malaria on Zanzibar, it turned to an unusual source to track the spread of the disease between the island and mainland Africa: mobile phones sold by Tanzania’s telecoms groups including Vodafone, the UK mobile operator.Working together with researchers at Southampton university, Vodafone began compiling sets of location data from mobile phones in the areas where cases of the disease had been recorded. Mapping how populations move between locations has proved invaluable in tracking and responding to epidemics. The Zanzibar project has been replicated by academics across the continent to monitor other deadly diseases, including Ebola in west Africa.“Diseases don’t respect national borders,” says Andy Tatem, an epidemiologist at Southampton who has worked with Vodafone in Africa. “Understanding how diseases and pathogens flow through populations using mobile phone data is vital.”
the best way to track the spread of the pandemic is to use heatmaps built on data of multiple phones which, if overlaid with medical data, can predict how the virus will spread and determine whether government measures are working.
Transport use during the coronavirus (COVID-19) pandemic. (n.d.). GOV.UK. Retrieved September 18, 2020, from https://www.gov.uk/government/statistics/transport-use-during-the-coronavirus-covid-19-pandemic
Graphs and maps from EUROMOMO. (n.d.). EUROMOMO. Retrieved September 18, 2020, from https://euromomo.eu/dev-404-page/
Svelte offers an immutable way — but it’s just a mask to hide “assignment”, because assignment triggers an update, but not immutability. So it’s enough to write todos=todos, after that Svelte triggers an update.
Like with React, you can pass in callback props like onSave and onDelete, which is the main way you send data out of a component to a parent.
COVID-19 reports. (n.d.). Imperial College London. Retrieved September 17, 2020, from http://www.imperial.ac.uk/medicine/departments/school-public-health/infectious-disease-epidemiology/mrc-global-infectious-disease-analysis/covid-19/covid-19-reports/
Giles, J. R., Erbach-Schoenberg, E. zu, Tatem, A. J., Gardner, L., Bjørnstad, O. N., Metcalf, C. J. E., & Wesolowski, A. (2020). The duration of travel impacts the spatial dynamics of infectious diseases. Proceedings of the National Academy of Sciences, 117(36), 22572–22579. https://doi.org/10.1073/pnas.1922663117
React is an isomorphic/universal framework. That means that there is a virtual representation of the UI component tree, and that is separate from the actual rendering that it outputs in the browser.
How to Export Your Content If you log into Graphite before August 15th, you can download each file in any of the available formats offered. If you'd like a bulk download, I recommend (for the technically inclined) using the exporter tool I created. For those less technically inclined, Blockstack may have some options for you. Remember, Graphite never owned your content. Never had control of your content. And that was the real power of its offering.
you should take care not to mutate the passed in value
Moreau, D., & Gamble, B. (2020). Conducting a meta-analysis in the age of open science: Tools, tips, and practical recommendations. Psychological Methods, No Pagination Specified-No Pagination Specified. https://doi.org/10.1037/met0000351
The COVID Tracking Project on Twitter. (n.d.). Twitter. Retrieved September 16, 2020, from https://twitter.com/COVID19Tracking/status/1304910646404739073
Krista Fischer on Twitter. (n.d.). Twitter. Retrieved September 15, 2020, from https://twitter.com/kristafischer16/status/1305145951955423233
Max Primbs on Twitter. (n.d.). Twitter. Retrieved September 14, 2020, from https://twitter.com/MaxPrimbs/status/1304516869509066760
Gollwitzer, M., Abele-Brehm, A., Fiebach, C., Ramthun, R., Scheel, A. M., Schönbrodt, F., & Steinberg, U. (2020). Data Management and Data Sharing in Psychological Science: Revision of the DGPs Recommendations. https://doi.org/10.31234/osf.io/24ncs
Finding data
You're right about data here. I follow some research out of the MIT Media lab by Cesar Hidalgo who may have some interesting data resources if you poke around.
Some additional starting points:
In this app, we have a <Hoverable> component that tracks whether the mouse is currently over it. It needs to pass that data back to the parent component, so that we can update the slotted contents. For this, we use slot props.
Stuart mcdonald on Twitter. (n.d.). Twitter. Retrieved September 10, 2020, from https://twitter.com/ActuaryByDay/status/1303719422595682306
Rajkumar, R. P. (2020). Novel Coronavirus Disease (COVID-19) and Suicide: Conceptual and Practical Considerations [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/z7drs
Spiegelhalter, D. (2020). Use of “normal” risk to improve understanding of dangers of covid-19. BMJ, 370. https://doi.org/10.1136/bmj.m3259
Susan Athey, July 22, 2020. (2020, August 2). https://www.youtube.com/watch?v=hqTOPrUxDzM
We wanted a library designed specifically for a functional programming style, one that makes it easy to create functional pipelines, one that never mutates user data.
Hu, Y., & Wang, R.-Q. (2020). Understanding the removal of precise geotagging in tweets. Nature Human Behaviour, 1–3. https://doi.org/10.1038/s41562-020-00949-x
COVID-19. (n.d.). Retrieved September 7, 2020, from https://covid19.healthdata.org/united-states-of-america?view=total-deaths&tab=trend
COVID Projections Tracker. (n.d.). Retrieved September 7, 2020, from https://www.covid-projections.com/
Johan Hellström on Twitter. (n.d.). Twitter. Retrieved September 7, 2020, from https://twitter.com/jhnhellstrom/status/1301073768748593153
NW, 1615 L. St, Suite 800Washington, & Inquiries, D. 20036USA202-419-4300 | M.-857-8562 | F.-419-4372 | M. (n.d.). A majority of young adults in the U.S. live with their parents for the first time since the Great Depression. Pew Research Center. Retrieved September 7, 2020, from https://www.pewresearch.org/fact-tank/2020/09/04/a-majority-of-young-adults-in-the-u-s-live-with-their-parents-for-the-first-time-since-the-great-depression/
Carozzi, F., Provenzano, S., Roth, S. (2020). Urban Density and Covid-19. Retrieved from http://cep.lse.ac.uk/pubs/download/dp1711.pdf
Had it not been for the attentiveness of one person who went beyond the task of classifying galaxies into predetermined categories and was able to communicate this to the researchers via the online forum, what turned out to be important new phenomena might have gone undiscovered.
Sometimes our attempts to improve data quality in citizen science projects can actually work against us. Pre-determined categories and strict regulations could prevent the reporting of important outliers.
COVID-19 Symptom Survey—Request for Data Access. (n.d.). Facebook Data for Good. Retrieved May 29, 2020, from https://dataforgood.fb.com/docs/covid-19-symptom-survey-request-for-data-access/
ReconfigBehSci on Twitter: “RT @ScottGottliebMD: See how quickly you can find Sweden on this map.... https://t.co/bhXACObtnQ” / Twitter. (n.d.). Twitter. Retrieved June 29, 2020, from https://twitter.com/scibeh/status/1276799757575315457
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This is probably one of the biggest things to get used to in React – this flow where data goes out and then back in.
Very good project ... really the best thought out data grid.
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Cluster 0 words: family, home, mother, war, house, dies, Cluster 0 titles: Schindler's List, One Flew Over the Cuckoo's Nest, Gone with the Wind, The Wizard of Oz, Titanic, Forrest Gump, E.T. the Extra-Terrestrial, The Silence of the Lambs, Gandhi, A Streetcar Named Desire, The Best Years of Our Lives, My Fair Lady, Ben-Hur, Doctor Zhivago, The Pianist, The Exorcist, Out of Africa, Good Will Hunting, Terms of Endearment, Giant, The Grapes of Wrath, Close Encounters of the Third Kind, The Graduate, Stagecoach, Wuthering Heights, Cluster 1 words: police, car, killed, murders, driving, house, Cluster 1 titles: Casablanca, Psycho, Sunset Blvd., Vertigo, Chinatown, Amadeus, High Noon, The French Connection, Fargo, Pulp Fiction, The Maltese Falcon, A Clockwork Orange, Double Indemnity, Rebel Without a Cause, The Third Man, North by Northwest, Cluster 2 words: father, new, york, new, brothers, apartments, Cluster 2 titles: The Godfather, Raging Bull, Citizen Kane, The Godfather: Part II, On the Waterfront, 12 Angry Men, Rocky, To Kill a Mockingbird, Braveheart, The Good, the Bad and the Ugly, The Apartment, Goodfellas, City Lights, It Happened One Night, Midnight Cowboy, Mr. Smith Goes to Washington, Rain Man, Annie Hall, Network, Taxi Driver, Rear Window, Cluster 3 words: george, dance, singing, john, love, perform, Cluster 3 titles: West Side Story, Singin' in the Rain, It's a Wonderful Life, Some Like It Hot, The Philadelphia Story, An American in Paris, The King's Speech, A Place in the Sun, Tootsie, Nashville, American Graffiti, Yankee Doodle Dandy, Cluster 4 words: killed, soldiers, captain, men, army, command, Cluster 4 titles: The Shawshank Redemption, Lawrence of Arabia, The Sound of Music, Star Wars, 2001: A Space Odyssey, The Bridge on the River Kwai, Dr. Strangelove or: How I Learned to Stop Worrying and Love the Bomb, Apocalypse Now, The Lord of the Rings: The Return of the King, Gladiator, From Here to Eternity, Saving Private Ryan, Unforgiven, Raiders of the Lost Ark, Patton, Jaws, Butch Cassidy and the Sundance Kid, The Treasure of the Sierra Madre, Platoon, Dances with Wolves, The Deer Hunter, All Quiet on the Western Front, Shane, The Green Mile, The African Queen, Mutiny on the Bounty,
The top IMDB films fit into 2 basic clusters, and 4 main clusters (this project used K-means with a target of 5 but actually clusters 1 and 2 both fit the crime category, and all except Cluster 3 are centred around violence).
If this list is representative of the human psyche we have only 2 basic modes of being: Violence / Musical.
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his dream of it being as easy to “insert facts, data, and models in political discussion as it is to insert emoji” 😉 speaks to a sort of consumerist, on-demand thirst for snippets, rather than a deep understanding of complexity. It’s app-informed, drag-and-drop data for instant government.
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