In May of this year, with the internet fully in the grip of the UK EU referendum, hashtags used on Instagram showed that discussion was highly polarised between #Leave and #Remain. The high degree of ideological distance between the two camps indicated that each group functioned as a separate ‘echo-chamber’, in which they spoke mainly to their own membership. The Leave campaign had a much more coherent online identity, made better use of hashtags in general, and was simply more active in generating content, all of which may have contributed to their successes. In early June 2016, a study of Twitter content found similar biases: Out of 1.5 million individual tweets, 54% were pro-Leave, and only 20% were pro-Remain. Those findings are interesting enough on their own, but what really sparked our interest, was that a third of the sampled content was created by only 1% of relevant user accounts.
If you’re not familiar with the inner workings of Twitter: No-one has that kind of time. It is highly unlikely that all of those accounts were directly controlled by people, or even large groups of people, and much more likely that many were staffed by automated software robots, or ‘bots’: Simple computer scripts that simulate highly repetitive human activity. In fact, an independent analysis of the 200 Twitter accounts which most frequently shared pro-Leave or pro-Remain content found that only 10% of those accounts were likely to be human.
The EU-referendum is not the first time ‘bots have been observed in democratic discussion. In the 2010 US midterm elections bots were actively used to support certain candidates and hamper others. In 2012 Lee Jasper admitted to their use in a parliamentary by-election. In the 2012 Mexican elections, Emiliano Treré identified a more effective use of bots, calling it “the algorithmic manufacturing of consent”, and a form of ‘ectivism’ (which includes the creation of large numbers of false followers, a charge levelled at Mitt Romney during the 2012 US Presidential election). A very large ‘bot-net’ was also utilised in 2013 to produce apparent support for a controversial Mexican energy reform. Those bots may have gone entirely unnoticed had they not been operating too rapidly to successfully pose as human agents.
Bot-related tactics have not been confined solely to the generation of apparent support, but have also been used to drown out members of a campaign by rendering their hashtags useless. The challenge presented by bots is not the introduction of false information, but the falsification of endorsement and popularity. Political discussions around the popularity of a single issue are particularly vulnerable, as are the financial implications of stock-confidence. During 2014 a bot-campaign elevated the value of tech-company Cynk from pennies to almost $5 billion USD in a few days. The company’s president, CEO, CFO, chief accounting officer, secretary, treasurer, and director were all the same individual: Marlon Luis Sanchez, Cynk’s sole employee. By the time Cynk’s stock-maneuver was discovered and its assets frozen Sanchez had made no additional profit, but for the investors who had been caught in the scheme, the losses were real.
Bot network detection research is being conducted by various defence agencies (including DARPA) but the field is complex, constantly changing, and yet to prove itself effective. Meanwhile, the deployment of bots on social media is within the terms of service for most of the relevant platforms, as long as no additional crime is committed their use is yet to face prosecution, and even in the case of Cynk no social media platform has assumed any kind of liability for their use.
The most active political users of social media are social movement activists, politicians, party workers, and those who are already fully committed to political causes, but recent evidence suggests that “bots” could be added to that list. Given the echo chamber effect, the fact that many online followers of political discourse are often not real users at all, and the steady decline in political participation numbers in many countries, bot use (while cheap to mobilise) may not have much power over the individual voter. Their deployment in the U.S. and Mexico has instead been largely targeted at journalists employed by mainstream media outlets. Politicians, activists, and party-workers may all find democratic scrutiny harder to achieve if the ‘public mood’ or ‘national conversation’ is being mis-reported by journalists with a bot-skewed sense of online discussion. The 2015 Global Social Journalism survey shows that in 51% of cases, reporters from six countries, including the UK and US, “would be unable to do their job without social media”. In 2012 38% of journalists spent up to two hours a day on various networks, but by 2015 that number had climbed to 57%. If unethical actors can unduly influence these avenues of online discourse, an increasingly vulnerable news-media may suffer from, and pass-on, the political biases of anonymous others.
If voting is affected by media, written by reporters who live on the internet, the shape of which is determined by anonymous, innumerable, automated agents (which no-one can track), how do we proceed in pursuit of a fair democracy?