A social bot (also: socialbot or socbot) is a particular type of chatbot that is employed in social media networks to automatically generate messages (e.g. tweets) or in general advocate certain ideas, support campaigns, and public relations either by acting as a "follower" or even as a fake account that gathers followers itself. In this respect, social bots can be said to have passed the Turing test.
Social bots appear to have played a significant role in the United States presidential election, 2016 and their history appears to go back at least to the United States midterm elections, 2010. It is estimated that 15% of the total Twitter population active in the US Presidential election discussion were bots. At least 400,000 thousand bots were responsible for about 3.8 million tweets, roughly 19% of the total volume. All these claims are disputed.
Twitterbots are already well-known examples, but corresponding autonomous agents on Facebook and elsewhere have also been observed. Nowadays, social bots can generate convincing internet personas that are well capable of influencing real people, although they are not always reliable.
Unless strict regulations on their use are passed, socialbots are expected to play a major role in future shaping of public opinion by autonomously acting as incessant and never-tiring influencers.
Lutz Finger identifies 5 immediate uses for social bots:
The effects of all points can be likened to and support methods of traditional psychological warfare.
The first generation of bots could sometimes be distinguished from real users by their often superhuman capacities to post messages around the clock (and at massive rates). Later developments have succeeded in imprinting more "human" activity and behavioural patterns in the agent. To unambiguously detect social bots as what they are, a variety of criteria must be applied together using pattern detection techniques, some of which are:
Botometer (formerly BotOrNot) is a public Web service that checks the activity of a Twitter account and gives it a score based on how likely the account is to be a bot. The system leverages over a thousand features. An active method that worked well in detecting early spam bots was to set up honeypot accounts where obvious nonsensical content was posted and then dumbly reposted (retweeted) by bots. Another method of detection is analysis of speed of change of the social network metrics: in particular, number of friends or followers for social bot grows very quickly, and clustering stays very low. That is explained by usage of "friend farm" services to collect large number of friends in a short period of time.
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