Want to know something mind blowing? It is estimated that there are over 20 million automated Twitter users (Kessler 2014). These ‘bots’, created by skilled programmers, are capable of re-tweeting, replying and even creating their own content.
Put simply, it’s relatively hard to spot a Bot. They become popular by tweeting in large quantities, following back those who follow them and targeting people that tweet about similar subjects that they’re designed to tweet about (Kessler 2014). They can amass large followings and, in extreme instances, inspire sympathy and conversation from those that follow them and read their content.
This is what happened to @trackgirl. ‘Her’ account is now suspended but the Bot, created by Greg Marra, would recycle tweets from runners and follow twitter profiles from within the long distance running community. 35% of users who @trackgirl followed followed her back. In mid 2008 she recycled a tweet saying she’d hurt her ankle and was inundated with messages, but public and private, inquiring about her injury and wishing her well (McMillan 2012).
Another high-profile example of Twitter Bots conning the public is @scarina91. Carina Santos, who claims to be a female journalist based in Rio de Janeiro, is actually a Bot, created by the computer science department at Brazil’s Federal University of Ouro Preto, that collects and tweets over 50 news alerts a day (Bosker 2013).
“Social bot attacks are actually about building a trust relationship” Marra explains, describing how these Bots can be used to build a relationship with fellow Twitter users and then flooding that user with (in some cases) spam, sales pitches and viruses. The invention of BimBots (Feifer 2012)- Twitter Bots that are designed to appear attractive to users – are particularly effective at this practice.
On a lighter note, these bots are among some of the funniest reads on the internet. I follow a couple of Bots that I’m aware of but it does make me wonder…Who online is really who they say they are?
Bosker, B 2013, ‘Twitter Bots Have No Trouble Fooling You, Getting More Influence Than Oprah’, The Huffington Post: Tech, 08/07/13, accessed at <http://www.huffingtonpost.com/2013/07/08/twitter-bots-influence_n_3542561.html>
Feifer, J 2012, ‘Who’s That Woman In The Twitter Bot Profile?’, Fast company, August 8 2012, accessed at <http://www.fastcompany.com/3000064/whos-woman-twitter-bot-profile>
McMillan, R 2012, ‘A Twitter bot so convincing that people sympathise with “her”‘, Wired UK, 26 June 2012, accessed at <http://www.wired.co.uk/news/archive/2012-06/26/twitter-bot-people-like>
Kessler, S 2014, ‘How Twitter Bots Fool You Into Thinking They Are Real People’, Fast Company, June 10 2014, accessed at <http://www.fastcompany.com/3031500/how-twitter-bots-fool-you-into-thinking-they-are-real-people>