But in our view, none adequately captures the full scope of recent changes that have taken place in contemporary politics. All of these labels highlight the increasing importance of data analytics in the operations of political parties, candidate campaigns, and issue advocacy efforts. Various terms have been used to describe and explain these practices - from computational politics to political micro-targeting to data-driven elections (Bodó, Helberger, & de Vreese, 2017 Bennett, 2016 Karpf, 2016 Kreiss, 2016 Tufekci, 2014). Our work is part of a growing body of interdisciplinary scholarship on the role of data and digital technologies in politics and elections. In two earlier papers, we documented a number of digital practices deployed during the 2016 elections, which were emblematic of how big data systems, strategies and techniques were shaping contemporary political practice (Chester & Montgomery, 2017, 2018). Kantar (2019), meanwhile, estimates the portion spent for digital media will be $1.2 billion USD in the 2019-2020 election cycle. In the upcoming 2020 election, experts are forecasting overall spending on political ads will be $6 billion USD, with an “expected $1.6 billion to be devoted to digital video… more than double 2018 digital video spending” (Perrin, 2019). Digital ad spending “quadrupled from 2014” to $950 million USD for ads that primarily ran on Facebook and Google (Axios, 2018 Lynch, 2018). These trends were clearly evident in the 2018 election, which, according to Kantar Media, were “the most lucrative midterms in history”, with $5.25 billion USD spent for ads on local broadcast cable TV, and digital - outspending even the 2016 presidential election. On the eve of the next presidential election in 2020, the pace of innovation in digital marketing continues unabated, along with its further expansion into US electoral politics. These recent legislative and regulatory initiatives in the US are narrow in scope and focused primarily on policy approaches to political advertising in more traditional media, failing to hold the tech giants accountable for their deleterious big data practices. Despite a great deal of public hand wringing, on the other hand, US federal policymakers have failed to institute any effective remedies even though several states have enacted legislation designed to ensure greater transparency for digital political ads (California Clean Money Campaign, 2019 Garrahan, 2018). Twitter and Google, driven by growing concern that they will be regulated for their political advertising practices, fearful of being found in violation of the General Data Protection Regulation (GDPR) in the European Union, and cognisant of their own culpability in recent electoral controversies, have each made significant changes in their political advertising policies (Dorsey, 2019 Spencer, 2019). In the wake of these cascading events, policymakers, journalists, and civil society groups have called for new laws and regulations to ensure transparency and accountability in online political advertising. The controversy also generated greater scrutiny of some of the most problematic tech industry practices - including the role of algorithms on social media platforms in spreading false, hateful, and divisive content, and the use of digital micro-targeting techniques for “voter suppression” efforts (Green & Issenberg 2016 Howard, Woolley, & Calo, 2018). The new revelations triggered a spate of congressional hearings and cast a spotlight on the role of digital marketing and “big data” in elections and campaigns. The scandal erupted amid ongoing concerns over Russian use of social media to interfere in the electoral process. In March 2018, The New York Times and The Guardian/Observer broke an explosive story that Cambridge Analytica, a British data firm, had harvested more than 50 million Facebook profiles and used them to engage in psychometric targeting during the 2016 US presidential election (Rosenberg, Confessore, & Cadwalladr, 2018). This paper is part of Data-driven elections, a special issue of Internet Policy Review guest-edited by Colin J.
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