"The key difference between this study and what has been done in the past, University of Sydney researcher @adamgdunn told ZDNet, is that it measures what people are looking at rather than just counting up what Twitter users are posting."
i.e. Carnegie Mellon get to fuck...
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A Carnegie Mellon study earlier this year found "almost half of the 200 million tweets posted about coronavirus from January to June were from bots"… …as long as you don't enquire too hard into their method for identifying bots, which is bunk & catches many new Twitter users.
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…and as long as you don't enquire too hard as to why exactly the number of bots posting about anything actually *matters*. If a bot tweets in the forest and nobody reads it, it isn't really influencing anything...
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“There is an assumption that the more bots that post, the more impact they have, but that’s not true,”
@adamgdunn said. “Thousands of tweets may never be seen if those accounts have no human followers. If you’re simply counting up bots, you’re not measuring reach or impact.”Show this thread -
This research does the thing that I have been wanting someone to do for ages, which is ~simulate users' timelines~ by collecting the tweets from the accounts they follow. And guess what? People generally don't follow many/any bots...
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Conclusion: “The overwhelming majority of the vaccine-related content seen by typical users in the US is generated by human-operated accounts, not bots.” And it comes from a small group, "5.8% of users who were embedded in communities where vaccine-critical content was common."
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Therefore “Rather than focussing on bots, we need to engage public health communication specialists whose aim is not to change opinions of vocal critics of vaccines, but to persuade silent observers of those critics and fence-sitters,”
@adamgdunn said.
https://www.theguardian.com/technology/2020/oct/02/twitter-bots-have-limited-success-spreading-anti-vaccination-messages …Show this thread
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