About a Bot: Hoax, Fake, Performance Art
Taina Bucher · M/C Journal · 2014
Introduction Automated or semi-automated software agents, better known as bots, have become an integral part of social media platforms. Reportedly, bots now generate twenty-four per cent of all posts on Twitter (Orlean “Man”), yet we know very little about who these bots are, what they do, or how to attend to these bots. This article examines one particular prominent exemplar: @Horse_ebooks, a much beloved Twitter bot that turned out not to be a “proper” bot after all. By examining how people responded to the revelations that the @Horse_ebooks account was in fact a human and not an automated software program, the intention here is not only to nuance some of the more common discourses around Twitter bots as spam, but more directly and significantly, to use the concept of persona as a useful analytical framework for understanding the relationships people forge with bots. Twitter bots tend to be portrayed as annoying parasites that generate “fake traffic” and “steal identities” (Hill; Love; Perlroth; Slotkin). According to such news media presentations, bots are part of an “ethically-questionable industry,” where they operate to provide an (false) impression of popularity (Hill). In a similar vein, much of the existing academic research on bots, especially from a computer science standpoint, tends to focus on the destructive nature of bots in an attempt to design better spam detection systems (Laboreiro et.al; Weiss and Tscheligi; Zangerle and Specht). While some notable exceptions exist (Gehl; Hwang et al; Mowbray), there is still an obvious lack of research on Twitter bots within Media Studies. By examining a case of “bot fakeness”—albeit in a somewhat different manner—this article contributes an understanding of Twitter bots as medium-specific personas. The case of @Horse_ebooks does show how people treat it as having a distinct personality. More importantly, this case study shows how the relationship people forge with an alleged bot differs from how they would relate to a human. To understand the ambiguity of the concept of persona as it applies to bots, this article relies on para-social interaction theory as developed by Horton and Wohl. In their seminal article first published in 1956, Horton and Wohl understood para-social interaction as a “simulacrum of conversational give and take” that takes place particularly between mass media users and performers (215). The relationship was termed para-social because, despite of the nonreciprocal exposure situation, the viewer would feel as if the relationship was real and intimate. Like theater, an illusory relationship would be created between what they called the persona—an “indigenous figure” presented and created by the mass media—and the viewer (Horton and Wohl 216). Like the “new types of performers” created by the mass media—”the quizmasters, announcers or ‘interviewers’” —bots too, seem to represent a “special category of ‘personalities’ whose existence is a function of the media themselves” (Horton and Wohl 216). In what follows, I revisit the concept of para-social interaction using the case of @Horse_ebooks, to show that there is potential to expand an understanding of persona to include non-human actors as well. Everything Happens So Much: The Case of @Horse_ebooks The case of the now debunked Twitter account @Horse_ebooks is interesting for a number of reasons, not least because it highlights the presence of what we might call botness, the belief that bots possess distinct personalities or personas that are specific to algorithms. In the context of Twitter, bots are pieces of software or scripts that are designed to automatically or semi-automatically publish tweets or make and accept friend requests (Mowbray). Typically, bots are programmed and designed to be as humanlike as possible, a goal that has been pursued ever since Alan Turing proposed what has now become known as the Turing test (Gehl; Weiss and Tschengeli). The Turing test provides the classic challenge for artificial intelligence, namely, whether a machine can impersonate a human so convincingly that it becomes indistinguishable from an actual human. This challenge is particularly pertinent to spambots as they need to dodge the radar of increasingly complex spam filters and detection algorithms. To avoid detection, bots masquerade as “real” accounts, trying to seem as human as possible (Orlean “Man”). Not all bots, however, pretend to be humans. Bots are created for all kinds of purposes. As Mowbray points out, “many bots are designed to be informative or otherwise useful” (184). For example, bots are designed to tweet news headlines, stock market quotes, traffic information, weather forecasts, or even the hourly bell chimes from Big Ben. Others are made for more artistic purposes or simply for fun by hackers and other Internet pundits. These bots tell jokes, automatically respond to certain keywords typed by other users, or write poems (i.e. @pentametron, @ProfJocular). Amidst the growing bot population on Twitter, @Horse_ebooks is perhaps one of the best known and most prominent. The account was originally created by Russian web developer Alexey Kouznetsov and launched on 5 August 2010. In the beginning, @Horse_ebooks periodically tweeted links to an online store selling e-books, some of which were themed around horses. What most people did not know, until it was revealed to the public on 24 September 2013 (Orlean “Horse”), was that the @Horse_ebooks account had been taken over by artist and Buzzfeed employee Jacob Bakkila in September 2011. Only a year after its inception, @Horse_ebooks went from being a bot to being a human impersonating a bot impersonating a human. After making a deal with Kouznetsov, Bakkila disabled the spambot and started generating tweets on behalf of @Horse_ebooks, using found material and text strings from various obscure Internet sites. The first tweet in Bakkila’s disguise was published on 14 September 2011, saying: “You will undoubtedly look on this moment with shock and”. For the next two years, streams of similar, “strangely poetic” (Chen) tweets were published, slowly giving rise to a devoted and growing fan base. Over the years, @Horse_ebooks became somewhat of a cultural phenomenon—an Internet celebrity of sorts. By 2012, @Horse_ebooks had risen to Internet fame; becoming one of the most mentioned “spambots” in news reports and blogs (Chen). Responses to the @Horse_ebooks “Revelation” On 24 September 2013, journalist Susan Orlean published a piece in The New Yorker revealing that @Horse_ebooks was in fact “human after all” (Orlean “@Horse_ebooks”). The revelation rapidly spurred a plethora of different reactions by its followers and fans, ranging from indifference, admiration and disappointment. Some of the sadness and disappointment felt can be seen clearly in the many of media reports, blog posts and tweets that emerged after the New Yorker story was published. Meyer of The Atlantic expressed his disbelief as follows: @Horse_ebooks, reporters told us, was powered by an algorithm. [...] We loved the horse because it was the network talking to itself about us, while trying to speak to us. Our inventions, speaking—somehow sublimely—of ourselves. Our joy was even a little voyeuristic. An algorithm does not need an audience. To me, though, that disappointment is only a mark of the horse’s success. We loved @Horse_ebooks because it was seerlike, childlike. But no: There were people behind it all along. We thought we were obliging a program, a thing which needs no obliging, whereas in fact we were falling for a plan. (Original italics) People felt betrayed, indeed fooled by @Horse_ebooks. As Watson sees it, “The internet got up in arms about the revelation, mostly because it disrupted our desire to believe that there was beauty in algorithms and randomness.” Several prominent Internet pundits, developers and otherwise computationally skilled people, quickly shared their disappointment and even anger on Twitter. As Jacob Harris, a self-proclaimed @Horse_ebooks fan and news hacker at the New York Times expressed it: Harris’ comparisons to the winning chess-playing computer Deep Blue speaks to the kind of disappointment felt. It speaks to the deep fascination that people feel towards the mysteries of the machine. It speaks to the fundamental belief in the potentials of machine intelligence and to the kind of techno-optimism felt amongst many hackers and “webbies.” As technologist and academic Dan Sinker said, “If I can’t rely on a Twitter bot to actually be a bot, what can I rely on?” (Sinker “If”). Perhaps most poignantly, Sinker noted his obvious disbelief in a blog post tellingly titled “Eulogy for a horse”: It’s been said that, given enough time, a million monkeys at typewriters would eventually, randomly, type the works of Shakespeare. It’s just a way of saying that mathematically, given infinite possibilities, eventually everything will happen. But I’ve always wanted it literally to be true. I’ve wanted those little monkeys to produce something beautiful, something meaningful, and yet something wholly unexpected.@Horse_ebooks was my monkey Shakespeare. I think it was a lot of people’s…[I]t really feels hard, like a punch through everything I thought I knew. (Sinker “Eulogy”) It is one thing is to be fooled by a human and quite another to be fooled by a “Buzzfeed employee.” More than anything perhaps, the question of authenticity and trustworthiness seems to be at stake. In this sense, “It wasn’t the identities of the feed’s writers that shocked everyone (though one of the two writers works for BuzzFeed, which really pissed people off). Rather, it was the fact that they were human in the first place” (Farago). As Sinker put it at the end of the “Eulogy”: I want to believe this wasn’t just yet another internet buzz-marketing prank.I want to believe that @Horse was as beautiful and wonderful today as it was yest