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Social and political bots have a small but strategic role in Venezuelan political conversations. These automated scripts generate content through social media platforms and then interact with people. In this preliminary study on the use of political bots in Venezuela, we analyze the tweeting, following and retweeting patterns for the accounts of prominent Venezuelan politicians and prominent Venezuelan bots. We find that bots generate a very small proportion of all the traffic about political life in Venezuela. Bots are used to retweet content from Venezuelan politicians but the effect is subtle in that less than 10 percent of all retweets come from bot-related platforms. Nonetheless, we find that the most active bots are those used by Venezuela’s radical opposition. Bots are pretending to be political leaders, government agencies and political parties more than citizens. Finally, bots are promoting innocuous political events more than attacking opponents or spreading misinformation.
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Suspensions of prominent accounts minimally impact platform engagement
Health-related misinformation online poses threats to individual well-being and undermines public health efforts. In response, many social media platforms have temporarily or permanently suspended accounts that spread misinformation, at the risk of losing traffic vital to platform revenue. Here we examine the impact on platform engagement following removal of six prominent accounts during the COVID-19 pandemic. Focused on those who engaged with the removed accounts, we find that suspension did not meaningfully reduce activity on the platform. Moreover, we find that removal of the prominent accounts minimally impacted the diversity of information sources consumed.
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- Award ID(s):
- 2120496
- PAR ID:
- 10524489
- Publisher / Repository:
- SocArxiv
- Date Published:
- Format(s):
- Medium: X
- Institution:
- University of Washington
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Posted Content:
- https://doi.org/10.31235/osf.io/x4jau
