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Facebook audience insights tool.

Facebook audience insights tool.

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Article
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Political campaigns increasingly rely on Facebook for reaching their constituents, particularly through ad targeting. Facebook's business model is premised on a promise to connect advertisers with the "right" users: those likely to click, download, engage, purchase. The company pursues this promise (in part) by algorithmically inferring users' inte...

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Context 1
... ad targeting categories appear in the Ads Manager within a loosely organized classification scheme featuring nine broad, top-level "topics" such as "Business and industry" and "Hobbies and activities" (see Figure 1). 3 The Audience Insights tool allows marketers to view rough estimates of how many individuals have been sorted into ad targeting categories, as well as other information about audiences, like location, demographics, Facebook pages users have liked, and past purchase behavior (see Figure 2). Facebook's Marketing API similarly allows third-parties to search the classification system and view all categories associated with a keyword, the exact number of individuals sorted into a category, and the higher level topics and "paths" into which categories fall (see Figure 3). ...
Context 2
... ad targeting categories appear in the Ads Manager within a loosely organized classification scheme featuring nine broad, top-level "topics" such as "Business and industry" and "Hobbies and activities" (see Figure 1). 3 The Audience Insights tool allows marketers to view rough estimates of how many individuals have been sorted into ad targeting categories, as well as other information about audiences, like location, demographics, Facebook pages users have liked, and past purchase behavior (see Figure 2). Facebook's Marketing API similarly allows third-parties to search the classification system and view all categories associated with a keyword, the exact number of individuals sorted into a category, and the higher level topics and "paths" into which categories fall (see Figure 3). ...

Citations

... ey promise to lower the cost of advertising and increase the efficiency of campaigns through detailed targeting, where advertisers can specify the users they would like to reach using a ributes (Danaher 2023;Kreiss 2011). However, it was shown (e.g., (Ali et al. 2021;Co er et al. 2021)) that targeting may not work as intended, and may shape the political ad delivery in ways that may not be beneficial to the political campaigns and to societal discourse. ...
Preprint
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Issue salience is a major determinant in voters' decisions. Candidates and political parties campaign to shift salience to their advantage - a process termed priming. We study the dynamics, strategies and equilibria of campaign spending for voter priming in multi-issue multi-party settings. We consider both parliamentary elections, where parties aim to maximize their share of votes, and various settings for presidential elections, where the winner takes all. For parliamentary elections, we show that pure equilibrium spending always exists and can be computed in time linear in the number of voters. For two parties and all settings, a spending equilibrium exists such that each party invests only in a single issue, and an equilibrium can be computed in time that is polynomial in the number of issues and linear in the number of voters. We also show that in most presidential settings no equilibrium exists. Additional properties of optimal campaign strategies are also studied.
... Nossos resultados corroboram pesquisas anteriores que têm evidenciado que conteúdos discriminatórios e/ou odiosos circulam nas plataformas da Meta, apesar das suas políticas de uso proibirem a circulação desse tipo de conteúdo (Cotter et al., 2021;Netlab UFRJ, 2024). No caso de anúncios, são necessárias medidas de transparência adicionais, já que políticos e a própria plataforma podem direcionar peças para segmentos vulneráveis do público. ...
Article
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Apesar de medidas para diminuir a prevalência de ataques a minorias sexuais e de gênero nas plataformas digitais, anúncios discriminatórios e odiosos têm sido patrocinados por políticos durante campanhas eleitorais ao redor do mundo. Este artigo analisa as estratégias discursivas e de segmentação de anúncios sobre a população LGBTQIAP+ nas plataformas da Meta durante a campanha eleitoral de 2022 para entender como os direitos dessa população foram instrumentalizados em um cenário político polarizado. Os pesquisadores coletaram 3.703 anúncios contrários e a favor dos direitos da comunidade LGBTQIAP+ veiculados no Brasil durante o primeiro turno e sistematizaram os dados de segmentação e investimento, além de analisarem o conteúdo veiculado pelos principais anunciantes. Anúncios anti-LGBTQIAP+ foram predominantes na campanha, recebendo mais investimento e alcançando um público maior que os conteúdos pró-LGBTQIAP+. Os resultados indicam que as medidas de governança promovidas pela Meta podem não ser suficientes para impedir a circulação de anúncios discriminatórios e odiosos.
... Interest bias in recommendation algorithms, although much more prevalent, is largely overlooked. That is, algorithms create narrow information diets, catering to users' preferences for football, K-pop, outrage, or clickbait, actively redirecting users away from news (19), and thus thwarting users'-especially the marginalized ones'-attention to matters of public interest (4,20,58). ...
Article
Full-text available
Recommendation algorithms profoundly shape users’ attention and information consumption on social media platforms. This study introduces a computational intervention aimed at mitigating two key biases in algorithms by influencing the recommendation process. We tackle \interest bias, or algorithms creating narrow non-news and entertainment information diets, and ideological bias, or algorithms directing the more strongly partisan users to like-minded content. Employing a sock-puppet experiment (N = 8,600 sock puppets) alongside a month-long randomized experiment involving 2,142 frequent YouTube users, we investigate if nudging the algorithm by playing videos from verified and ideologically balanced news channels in the background increases recommendations to and consumption of news. We additionally test if providing balanced news input to the algorithm promotes diverse and cross-cutting news recommendations and consumption. We find that nudging the algorithm significantly and sustainably increases both recommendations to and consumption of news and also minimizes ideological biases in recommendations and consumption, particularly among conservative users. In fact, recommendations have stronger effects on users’ exposure than users’ exposure has on subsequent recommendations. In contrast, nudging the users has no observable effects on news consumption. Increased news consumption has no effects on a range of survey outcomes (e.g., knowledge, participation, polarization, misperceptions), adding to the growing evidence of limited attitudinal effects of on-platform exposure. The intervention does not adversely affect user engagement on YouTube, showcasing its potential for real-world implementation. These findings underscore the influence wielded by platform recommender algorithms on users’ attention and information exposure.
... A similar view is also put forward by Shepard (2022, p. 3) who stresses that as algorithms 'maximize user engagement through shares and likes', they end up 'promoting the proliferation of post-truth terrain across the network'. In particular, the ability to algorithmically micro-target users with digitally manufactured content is seen as a major new threat (Cotter et al., 2021;Dobber et al., 2021;Thorson et al., 2021). The net result then could be the creation of a fake impression of consensus within an in-group (Chadwick & Stanyer, 2022), resulting in the development of a false view of the world and a shared reality, audience understanding of their self-interest, notions of right and wrong, stirring up specific emotions-all of that for the benefit of those in control of or with access to the technological means of directing the flow of information (Susskind, 2018, p. 143). ...
Chapter
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Today’s most prominent discussions of post-truth are united by a kernel of nostalgia, framing the present time as one of cognitive and moral decay and as open to abuse by populists. Meanwhile, this chapter demonstrates that the true object of nostalgia is, instead, the detached and disembodied rational Cartesian subject. Hence, instead of diagnosing the problems facing today’s societies, the mainstream discourse on post-truth manifests close affinities with its own object of critique—(frequently nostalgic) populism. Instead of focusing on a singular truth that has to be made great again, the political landscape postulated in this chapter is one populated by a multitude of truth-utterances, interrelating with each other on a groundless terrain without the possibility of an ultimate fixed order or grounding truth in what is conceptualized as the tragic domain of politics. Only then, it is argued, can a truly pluralist account of political discourse be embraced.
... The proliferating algorithmic identities they produce about consumers are likely to change with the evolution of the data collection and algorithmic calculation (Cheney-Lippold, 2017), resulting in ever-changing categorizations and sorting of consumers. In the case of the Facebook Ad Manager, these data-driven categories, referred to as "interest" categories, are built algorithmically from several inputs: they are "translated" from users' explicit behaviors (liking a page) and "imputed" from their browsing traces; the categories also evolve according to the uses and the feedbacks of the advertisers (Cotter et al., 2021;García Martínez, 2016). ...
... The surveillance analysis rightly focuses on the sheer amount of personal data that is routinely collected by marketing professionals and put into circulation in the advertising ecosystem (Christl, 2017;Crain, 2019). It adequately describes the potential use of this marketing data by state surveillance actors (Lyon, 2014) and the increased risk of using Facebook advertising tools to discriminate against people and fabricate sensitive or illegal audience segments (Ali et al., 2019a;Angwin et al., 2017;Cabañas et al., 2018;Cotter et al., 2021). ...
Article
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Recent innovations in online advertising facilitate the use of a wide variety of data sources to build micro-segments of consumers, and delegate the manufacture of audience segments to machine learning algorithms. Both techniques promise to replace demographic targeting, as part of a post-demographic turn driven by big data technologies. This article empirically investigates this transformation in online advertising. We show that targeting categories are assessed along three criteria: efficiency, communicability, and explainability. The relative importance of these objectives helps explain the lasting role of demographic categories, the development of audience segments specific to each advertiser, and the difficulty in generalizing interest categories associated with big data. These results underline the importance of studying the impact of advanced big data and AI technologies in their organizational and professional contexts of appropriation, and of paying attention to the permanence of the categorizations that make the social world intelligible.
... An example would be "inferred interests" for advertisements (example file from Instagram DDPs). Without contextual information on classification algorithms, it is difficult for users to understand such data (Cotter et al., 2021;Rieder & Hofmann, 2020 Table A3), researchers cannot correct such errors because they do not know how measurements were created. ...
Article
Full-text available
Research into digital platforms has become increasingly difficult. One way to overcome these difficulties is to build on data access rights in EU data protection law, which requires platforms to offer users a copy of their data. In data donation studies, researchers ask study participants to exercise this right and donate their data to science. However, there is increasing evidence that platforms do not comply with designated laws. We first discuss the obligations of data access from a legal perspective (with accessible, transparent, and complete data as key requirements). Next, we compile experiences from social scientists engaging in data donation projects as well as a study on data request/access. We identify 14 key challenges, most of which are a consequence of non-compliance by platforms. They include platforms’ insufficient adherence to (a) providing data in a concise and easily accessible form (e.g. the lack of information on when and how subjects can access their data); (b) being transparent about the content of their data (e.g. the lack of information on measures); and (c) providing complete data (e.g. the lack of all available information platforms process related to platform users). Finally, we formulate four central recommendations for improving the right to access.
... Social media allows behavioural targeting by political parties to persuade the masses (Schäwel et al., 2021). Facebook's business framework is based on the interest categorization system, which works to build on conversations by algorithmically inferring from users' data by providing tools for advertisers (Cotter et al., 2021). Facebook-sponsored content is dominated mainly by three text patterns: mobilization, candidate accounts and ideological supporters (Baviera et al., 2022). ...
... those parties with no potential coalitions become easy targets for negative campaigns (Papp & Patkós, 2018). For such campaigns, considering the subject by a data-driven system shapes possibilities for representation and political voice for specific segments depending upon race, colour, gender, and lGBtQ+ people (Cotter et al., 2021). Political advertisements have different gender candidates with certain kinds of body language; compared to female candidates, male candidates use more assertive hand gestures (neumann et al., 2022). ...
Article
Full-text available
Political advertising on social media has increased dramatically in the last several years, reaching specific audiences with tailored messages. Political advertising is characterized by its primary objective, which is to attract voters through various means by a candidate, politician, or political party. By analyzing existing communication patterns that appeal to the general public during the electoral process, this study seeks to develop an intellectual framework that considers linguistic discourse. Using bibliometric analysis, this study examines and evaluates the body of literature on political advertising and how it is disseminated. It includes 114 publications published between 1996 and 2024 in the Scopus and WOS databases and were subjected to keyword analysis in the VOS viewer. This analysis produced six clusters, which eventually combined under three overarching themes. The results showed that the few previous studies conducted in this field only focused on the election season and that direct political actors were the source of these advertisements. More research on the sociopolitical context is desperately needed, along with scientific solutions, to address privacy concerns on digital platforms and disinformation in dialogic discourse. Considering all possible complexities in the persuasive communication process, this article offers concrete directions and propositions on efficiently targeting voters and implementing future regulations.
... Since ads are not public and their respective targeting strategies are opaque, they can cause or exacerbate various social problems. For instance, [14], [40] and [63] have indicated that digital advertising systems can reinforce stereotypes, alienate voters, and aggravate social inequalities. ...
Conference Paper
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Digital platforms provide a deregulated and opaque environment suited to the maintenance of their business model, in which ads are efficiently served by opaque algorithms to meticulously profiled users based on their behavioral data. The advertising infrastructure provided by these platforms made advertising more segmented and scalable, creating new opportunities and allowing for a profit-oriented influence industry to develop worldwide. Some platforms have invested in transparency measures for digital advertising, but there is still a gap between what is applied in the Global South and the Global North. In Brazil, despite evidence of an online ecosystem of suspicious, inauthentic, scam, and other types of fraudulent ads, regulatory proposals have faced a hard opposition from tech companies. Against this backdrop, there is a need to evaluate advertising transparency archives currently offered by online platforms in Brazil as a means to measure the quality of libraries and the available data. Thus, the main objective of this work is to account for transparency measures and means of accessing data of some of the largest online platforms and search engines in the country, in order to establish a general comparative diagnosis of ad transparency in Brazil. Based on the platforms' public documentation, policies and terms of use for the Brazilian market, we perform a comparative analysis of six companies: Meta, Google, Twitter/X, Telegram, TikTok, and Spotify. Particular consideration is given to whether these companies do or do not have ads repositories, or a means to assess the disseminated advertisements. In an environment of low transparency and difficulty in accessing data, we found that the Meta Ad Library, although providing very limited data, is the most reliable source for systematic investigations of the digital advertising ecosystem. Even though Google offers an advertisement repository in Brazil, it lags considerably behind that offered by Meta and imposes greater difficulty in carrying out systematic analyses. On the other hand, Telegram, TikTok, Twitter/X and Spotify do not present any advertising repository or transparency center in order to analyse the Brazilian scenario. Although the scenario in the This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs International 4.0 License. Global South can be characterized by a lack of transparency from platforms and by difficulties in accessing data, recent measures implemented elsewhere have demonstrated that this condition is reversible. CCS CONCEPTS • Information systems → Information systems applications; Computational advertising; Information systems applications; Digital libraries and archives; • Human-centered computing → Collab-orative and social computing; Collaborative and social computing systems and tools; Social networking sites.
... Perceptions of social media have evolved, however, and are increasingly gaining a security context for several reasons, including privacy concerns. Social media platforms collect and store troves of information about their users, which are then monetized by promising to connect advertisers with the closely matched users (Cotter et al., 2021), including in political campaigning. ...
... The now defunct company used personal user data to build psychographic user profiles (Garcia-Diaz et al., 2022;Kanakia et al., 2019) and influence voting preferences through tailored advertising (Hinds et al., 2020). Brad Pascarle, digital media director for Donald Trump's successful 2016 presidential campaign, claimed that targeting highly specific clusters of voters daily on Facebook helped win the election (Cotter et al., 2021). On Facebook, users are grouped into different 'interest' categories, that are then sold to advertisers. ...
Article
Full-text available
Russia’s cyber-enabled influence operations (CEIO) have garnered significant public, academic and policy interest. 126 million Americans were reportedly exposed to Russia’s efforts to influence the 2016 US election on Facebook. Indeed, to the extent that such efforts shape political outcomes, they may prove far more consequential than other, more flamboyant forms of cyber conflict. Importantly, CEIOs highlight the human dimension of cyber conflict. Focused on ‘hacking human minds’ and affecting individuals behind keyboards, as opposed to hacking networked systems, CEIOs represent an emergent form of state cyber activity. Importantly, data for studying CEIOs are often publicly available. We employ semantic network analysis (SNA) to assess data seldom analyzed in cybersecurity research – the text of actual advertisements from a prominent CEIO. We examine the content, as well as the scope and scale of the Russian-orchestrated social media campaign. While often described as ‘disinformation,’ our analysis shows that the information utilized in the Russian CEIO was generally factually correct. Further, it appears that African Americans, not white conservatives, were the target demographic that Russia sought to influence. We conclude with speculation, based on our findings, about the likely motives for the CEIO.
... Some of these categories are organic, based on the names of followed pages, hashtags, and other user keywords. Others are created by Meta -they are requested by industry or composited based on Meta's own research and analysis of user behaviour (Cotter, et al., 2021). We set out some of these mechanisms in Figure 1. ...
... We set out some of these mechanisms in Figure 1. This business model, often summarised as surveillance capitalism (Zuboff, 2019), allows a move beyond traditional postcode, demographic, and consumption pattern segmentation to tailored campaigns that address people in groups based on detailed behaviours, interests, and real time location data (Cotter, et al., 2021). The mechanisms by which this targeting is facilitated involve a huge intermediary industry of data sources and algorithmic imputation of interests and behaviours (often branded as AI) (van der Vlist and Helmond, 2021). ...
... Audiences can be filtered on including and excluding people based on these categories. On most platforms, exclusionary targeting using direct selection of categories that include protected characteristics ("Muslim", "gay") has been significantly reduced in recent years by filtering thousands of keywords, and platforms continually merge or consolidate categories (Cotter, et al., 2021) [4]. There has been increasing disapproval of targeting directly on multicultural affinity constructs such as 'African American'. ...
Article
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The targeted digital advertising infrastructures on which the business models of the social media platform economy rest have been the subject of significant academic and political interest. In this paper, we explore and theorise the appropriation of these infrastructures — designed for commercial and political advertising — by the state. In the U.K., public sector bodies have begun to repurpose the surveillance and messaging capacities of these social media platforms, along with the influencer economy, to deliver targeted behaviour change campaigns to achieve public policy goals. We explore how frameworks of behavioural government have aligned with Internet platforms’ extensive infrastructures and the commercial ecologies of professionalised strategic marketing. We map the current extent of these practices in the U.K. through case studies and empirical research in Meta’s Ad Library dataset. Although the networks of power and discourse within the ad infrastructure are indeed acting to shape the capacities of the state to engage in online influence, public bodies are mobilising their own substantial material networks of power and data to re-appropriate them to their own ends. Partly as a result of attempts by Meta to restrict the targeting of protected characteristics, we observe state communications campaigns building up what we term patchwork profiles of minute behavioural, demographic, and location-based categories in order to construct and reach particular groups of subjects. However, rather than a clear vision of a ‘cybernetic society’ of reactive information control, we instead find a heterogeneous and piecemeal landscape of different modes of power.