rvenkat + bots   15

Bots increase exposure to negative and inflammatory content in online social systems | PNAS
Social media can deeply influence reality perception, affecting millions of people’s voting behavior. Hence, maneuvering opinion dynamics by disseminating forged content over online ecosystems is an effective pathway for social hacking. We propose a framework for discovering such a potentially dangerous behavior promoted by automatic users, also called “bots,” in online social networks. We provide evidence that social bots target mainly human influencers but generate semantic content depending on the polarized stance of their targets. During the 2017 Catalan referendum, used as a case study, social bots generated and promoted violent content aimed at Independentists, ultimately exacerbating social conflict online. Our results open challenges for detecting and controlling the influence of such content on society.
bots  misinformation  disinformation  networked_public_sphere  journalism  via:nyhan 
november 2018 by rvenkat
The Brexit Botnet and User-Generated Hyperpartisan NewsSocial Science Computer Review - Marco T. Bastos, Dan Mercea, 2017
In this article, we uncover a network of Twitterbots comprising 13,493 accounts that tweeted the United Kingdom European Union membership referendum, only to disappear from Twitter shortly after the ballot. We compare active users to this set of political bots with respect to temporal tweeting behavior, the size and speed of retweet cascades, and the composition of their retweet cascades (user-to-bot vs. bot-to-bot) to evidence strategies for bot deployment. Our results move forward the analysis of political bots by showing that Twitterbots can be effective at rapidly generating small- to medium-sized cascades; that the retweeted content comprises user-generated hyperpartisan news, which is not strictly fake news, but whose shelf life is remarkably short; and, finally, that a botnet may be organized in specialized tiers or clusters dedicated to replicating either active users or content generated by other bots.

a dilute version here

https://www.city.ac.uk/news/2017/october/13,500-strong-twitterbot-army-disappeared-shortly-after-eu-referendum,-research-reveals

and here

https://www.buzzfeed.com/jamesball/a-suspected-network-of-13000-twitter-bots-pumped-out-pro?utm_term=.sdR6KZ1BOr
bots  european_politics  artificial_intelligence  social_media  social_networks  twitter  public_opinion  public_sphere  cybersecurity  international_affairs  via:henryfarrell  networks  teaching 
october 2017 by rvenkat

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