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  1. Last 7 days
    1. This came in the context of weighing what she stood to gain and lose in leaving a staff job at BuzzFeed. She knew the worth of what editors, fact-checkers, designers, and other colleagues brought to a piece of writing. At the same time, she was tired of working around the “imperatives of social media sharing.” Clarity and concision are not metrics imposed by the Facebook algorithm, of course — but perhaps such concerns lose some of their urgency when readers have already pledged their support.

      Continuing with the idea above about the shift of Sunday morning talk shows and the influence of Hard Copy, is social media exerting a negative influence on mainstream content and conversation as a result of their algorithmic gut reaction pressure? How can we fight this effect?

  2. Jun 2021
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    1. Jefferson, T., Jones, M., Al Ansari, L. A., Bawazeer, G., Beller, E., Clark, J., Conly, J., Del Mar, C., Dooley, E., Ferroni, E., Glasziou, P., Hoffman, T., Thorning, S., & Van Driel, M. (2020). Physical interventions to interrupt or reduce the spread of respiratory viruses. Part 1 - Face masks, eye protection and person distancing: Systematic review and meta-analysis [Preprint]. Public and Global Health. https://doi.org/10.1101/2020.03.30.20047217

  13. Jan 2019
  14. static1.squarespace.com static1.squarespace.com
    1. Uh, yeah, I'm in a few groups. There's a couple of the crypto focused, uh, the also have been just, I wouldn't say [inaudible], but have put more emphasis on, you know, since we're technical traders, there's a reason not to take advantage of, uh, the market opportunities and traditional as they pop up. So we've been focused mainly on just very few inverse etfs to short the s&p to short some major Chinese stocks, um, doing some stuff with, uh, oil, gas. And then there's some groups that I'm in that are specifically focused on just traditional, uh, that are broken up or categorized by what they're trading.
  15. Aug 2018
    1. 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.
  16. Jul 2018
    1. 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.
    2. 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.
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