Engineering victory and defeat: the role of social bots on Twitter during the French PresidentialElections
Résumé
The electoral campaigns of both Trump and Macron took place in a climate marked by accusations of “fake news”, manipulation of social media and personal attacks. Previous research has even shown that the same automated Twitter accounts were used to spread rumours to discredit both Hillary Clinton and later Emmanuel Macron, notably during the “Macron Leaks” scandal (Ferrara, 2017), which has led to accusations of orchestrated foreign infiltration in at least the French presidential campaign. Although it is difficult to distinguish (legitimate) foreign discussions of (rumours related to) French presidential candidates on Twitter on the one hand and intentional meddling in national politics on the other, it has been suggested that such foreign interference is becoming common practice worldwide (Woolley & Howard, 2017). Discussions on social networking sites (SNS) have become an important focus of political debate and are sometimes taken as a preliminary indicator of public opinion by mainstream media. Their manipulation involves the use of “social robots” (bots). “A social bot is a defined as “computer algorithm that automatically produces content and interacts with humans on social media, trying to emulate and possibly alter their behavior.” (Ferrara, Varol, Davis, Menczer, & Flammini, 2016, p. 96).Research in computer science has proposed various methods to detect social bots on Twitter (Clark et al., 2016; Danisch, Dugué, & Perez, 2014; Davis, Varol, Ferrara, Flammini, & Menczer, 2016; Dickerson, Kagan, & Subrahmanian, 2014; Edwards, Edwards, Spence, & Shelton, 2014). Although studies suggest that bots are in many cases still detectable in the field of political propaganda (Grimme, Preuss, Adam, & Trautmann, 2017), other research warns that these algorithms are becoming increasingly complex and able to replicate human behaviour through machine learning (Ferrara et al., 2016, p. 99). Social bots are now widely used in various contexts, including political communication, and notably during election campaigns (Woolley & Howard, 2016), especially on Twitter. Research has shown that social bots were used on Twitter during the 2016 US presidential election, for example to spread links to fake news websites (P. N. Howard, Bolsover, Kollanyi, Bradshaw, & Neudert, 2017), and have been estimated responsible for up to one fifth of campaign-related content produced in the lead-up to Trump’s victory (Bessi & Ferrara, 2016). They were also used in the 2017 French presidential elections (Ferrara, 2017; P. N. Howard, Bradshaw, Kollanyi, & Bolsolver, 2017a, 2017b), in the Brexit referendum campaign (P. Howard & Kollanyi, 2016), and in recent elections in Venezuela (Forelle, Howard, Monroy-Hernandez, & Savage, 2015) and Russia (Stukal, Sanovich, Bonneau, & Tucker, 2017), among many others. Bots can be used to diffuse or relay large quantities of positive or negative content pertaining to a candidate or political movement, spread rumours or links to “junk news” or “fake news” websites, though some research suggests that their impact on human interactions may remain limited (Murthy et al., 2016). Bots are also used to create automated followers or politicians’ or parties’ accounts, another common practice in US , French (Boyadjian, 2015) and other elections. Finally, discussions on SNS during election campaigns include messages generated by news bots, which may affect the information being spread, even when not having been intentionally programmed to favour one candidate or another (Lokot & Diakopoulos, 2016). This contribution aims to further research into this new dimension of electronic electioneering, which requires interdisciplinary approaches. Based on a study involving research teams in both communication science and computer science, working from a corpus of approximately 50M election-related tweets collected over five weeks in April and May 2017, and in the light of previous research into the “Macron Leaks” scandal (Ferrara, 2017) and use of campaign-bots in the US presidential elections (Bessi & Ferrara, 2016), it will (i) identify the presence of likely social bots on Twitter during the French presidential elections, and (ii) measure and analyse their activity pertaining to the two candidates between the first and second rounds of the election. References:Bessi, A., & Ferrara, E. (2016). Social Bots Distort the 2016 US Presidential Election Online Discussion (SSRN Scholarly Paper No. ID 2982233). Rochester, NY: Social Science Research Network. Boyadjian, J. (2015). Les usages frontistes du web. In S. Crépon, A. Dézé, & N. Mayer (Eds.), Les faux-semblants du Front national (pp. 141–160). 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