Selected Papers of #AoIR2022: The 23rd Annual Conference of the Association of Internet Researchers Dublin, Ireland / 2-5 Nov 2022 Suggested Citation (APA): Bruns, A., Schumacher, N.F., Mathieu, M., Nuernbergk, C., Righetti, N., Giglietto, F., Kakavand, A., Kulichkina, A., Marino, G., Terenzi, M., Angus, D., Graham, T., Dehghan, E., Jude, N., Matich, P., Andrejevich, M., Carlson, B., Obeid, A., Mai, P., & Gruzd, A. (2022, November). Pandemic Politics: The 2021 and 2022 German and Australian Federal Election Campaigns on Social Media. Panel presented at AoIR 2022: The 23rd Annual Conference of the Association of Internet Researchers. Dublin, Ireland: AoIR. Retrieved from http://spir.aoir.org. PANDEMIC POLITICS: THE 2021 AND 2022 GERMAN AND AUSTRALIAN FEDERAL ELECTION CAMPAIGNS ON SOCIAL MEDIA Axel Bruns Digital Media Research Centre, Queensland University of Technology Nina Fabiola Schumacher Media Studies, Trier University Moritz Mathieu Media Studies, Trier University Christian Nuernbergk Media Studies, Trier University Nicola Righetti University of Vienna Fabio Giglietto University of Urbino Carlo Bo Azade Kakavand University of Vienna Aytalina Kulichkina University of Vienna Giada Marino University of Sassari Massimo Terenzi University of Urbino Carlo Bo Daniel Angus Digital Media Research Centre, Queensland University of Technology Timothy Graham Digital Media Research Centre, Queensland University of Technology Ehsan Dehghan Digital Media Research Centre, Queensland University of Technology Nadia Jude Digital Media Research Centre, Queensland University of Technology Phoebe Matich Digital Media Research Centre, Queensland University of Technology Mark Andrejevic School of Media, Film, and Journalism, Monash University Bronwyn Carlson Department of Indigenous Studies, Macquarie University Abdul Obeid Digital Media Research Centre, Queensland University of Technology Philip Mai Social Media Lab, Ryerson University Anatoliy Gruzd Social Media Lab, Ryerson University Panel Introduction One of the effects of the continuing COVID-19 pandemic has been to further accelerate the incorporation of social media activities into political and electoral campaigning. Especially as a result of lockdowns and other restrictions to offline public life, overall social media use has increased in many countries; health concerns have severely curtailed conventional in-person political campaigning activities, from doorknocking to mass rallies (even if some candidates are openly flouting health measures in order to appeal to fringe, COVID-denialist voters); and concerns about the safety of in-person voting processes have also led to a growth in postal voting well ahead of election day, potentially increasing the importance of political messaging early on in election campaigns. In addition, of course, the pandemic itself, and the health, economic, and social measures taken by different governments to address and manage its implications, have also become a dominant theme in most political contests. Political parties around the world have scrambled to keep up with and engage with these changing circumstances, voter behaviours, and political debates, and it is therefore time to re-examine the current state of affairs. This panel does so by focussing on social media campaigning in two of the most recent major national elections: the German federal election campaign in August and September 2021, and the Australian federal election campaign in March to May 2022. The four papers included in this panel examine political campaigning, public engagement, and journalistic coverage on Facebook and Twitter, as well as political advertising practices on Facebook, and in combination offer a very timely new perspective on electioneering in the final stages of a multi-year global pandemic. The first two papers address the German federal election in September 2021. Paper 1 focusses on the use of Twitter, as a comparatively elite medium, by hundreds of federal politicians and the members of the federal press corps or Bundespressekonferenz. For the periods before and during the campaign, it studies the activities of both groups, their intra- and inter-group interaction networks, and the themes of their posts. Over the timeframe of the study, this especially highlights the dynamics of both groups’ activities. Paper 2 complements this work by investigating advertising practices on Facebook during the German federal election campaign. Drawing on the Facebook Ad Library, its dataset of more than 20,000 advertisements offers an insight into the advertising spending and targeting practices of the major parties contesting the election. This provides an important new update on the use of such campaigning tools in German federal politics, but also highlights some of the continuing limitations of the Ad Library as a single source of data on political advertising and targeting practices on Facebook. The other two papers focus on the Australian federal election, to be held in March to May 2022. Paper 3 continues a series of systematic election analyses going back almost a decade: as in 2013, 2016, and 2019, it tracks the Twitter activities of all candidates, as well as the engagement they receive from other accounts, but in a further adaptation of this approach it now extends this analysis also to the activities of and engagement with the candidates’ Facebook pages. By assessing overall posting and engagement patterns, examining themes in posts and responses, and identifying evidence of organic or inauthentic coordinated behaviours, the paper offers a comprehensive overview of the social media campaign in the 2022 federal election. Paper 4, finally, again complements the preceding study of social media activity with a detailed investigation of political advertising practices on Facebook. This takes a two- pronged approach: using the PoliDashboard tool, it captures and analyses the political advertisements revealed by Facebook’s own Ad Library. The paper then compares and contrasts this dataset with the actual political advertising encountered by volunteer participants in the Australian Ad Observatory, a browser-side ad tracking tool that builds on the infrastructure of the NYU Ad Observatory and the ProPublica Political Ad Collector. This especially enables the researchers to detect any advertising campaigns that carry political messaging but have avoided a classification as ‘political’ in the Ad Library. In combination, then, these four papers provide an in-depth insight into contemporary, pandemic-era campaigning practices, dynamics, and themes in two of the most recent major national elections, across key social media platforms such as Facebook and Twitter, and take into account both organic posting activity and paid advertising efforts. They make a timely contribution to our evolving understanding of political campaigning on social media. The extended abstracts for the four individual papers follow on the next pages. Paper 1: COMPARING POLITICAL COVERAGE ON TWITTER: THE GERMAN ELECTION CAMPAIGN 2021 THROUGH THE LENS OF JOURNALISTS AND POLITICIANS Nina Fabiola Schumacher Media Studies, Trier University Moritz Mathieu Media Studies, Trier University Christian Nuernbergk Media Studies, Trier University Introduction & Research Overview Since the 2013 election, social media has become a common campaign practice in German campaign communication. The 2017 election is considered the first digital election in which a broad range of new formats was experimented with and used for professional staging and “image building” (Holtz-Bacha 2019). The 2021 election has been dominated by the COVID-19 pandemic. Therefore, most political events and discussions occurred online. New hybrid formats have emerged. Thus, the pandemic has accelerated digitalization and given digital debates more impact (Vowe 2021). Nowadays, web-based campaigns are ubiquitous, accelerating the professionalization of elections and campaigns, which include and request active political participation (Fitzpatrick & Jöst 2021). In addition to its widespread use among political and other societal actors, Twitter is an integral part of journalistic practice (Molyneux & Mourão 2019) to obtain and distribute news and information in real-time, to connect with other users, or to monitor what they say. Twitter is part of a hybrid and multimodal communication environment that has eroded the monopoly on public information once held by news media professionals (Chadwick 2017). Consequently, Twitter use by political-media actors affects information flows, news production routines, agenda setting, framing processes, and the relationship of journalists and politicians (Broersma & Graham 2015). The body of available research regarding campaign patterns on Twitter is substantive (Corchia 2019; Jungherr 2015). Various studies indicate how and to what extent politicians use microblogging by exploring party differences (Larsson 2017). However, research comparing election and non-election campaign periods (e.g., Nuernbergk & Conrad 2016) is less prominent. Concerning political coverage, studies primarily focus on traditional media channels (Leidecker-Sandmann & Wilke 2019) or behavior of journalists during campaign events (Mourão 2015). That said, research comparing journalists and candidates/MPs seems particularly rare (Corchia 2019). Thus, this study will examine sitting German MPs and journalists registered in the Federal Press Conference (BPK) through a comparative analysis of their Twitter updates and interactions during the 2021 election. In particular, the following research questions guide this comparison of journalists and MPs: ● RQ1: How do the Twitter activity patterns evolve in both groups and what campaign references do they exhibit? ● RQ2: How do both groups refer to and evaluate leading candidates? ● RQ3: To what extent do both groups refer to non-campaign topics or comment on more permanent issues (such as the pandemic)? ● RQ4: With whom do both groups interact and in what structural network patterns does this result? We answer all RQs by comparing a pre-campaign period and a campaign period. We will also highlight differences by party affiliation and sectoral differences (commercial vs. public service media). Data & Methodology For this study, we followed an accounts-centered approach; our monitoring of both account groups lasted from May to September 2021. First, we searched the BPK directory and the German Bundestag for Twitter accounts and user IDs, which were needed for API-based tracking. Second, we tracked MPs and journalists continuously using the DMI TCAT (Borra & Rieder 2014). The German election took place on September 26th. Specifically, we examine the periods pre-campaign (24.5.–8.8.21) and campaign (9.8.–27.9.21). Thus, the campaign period comprises six weeks before the election, the Election Day, and the day afterward. We grouped journalists according to their sectoral affiliation and MPs according to their political party. We combine the tracking data with this information. Beyond analyzing the activity patterns and typical statistics, we also conduct a network analysis. Therefore, we computed network graphs based on @mentions and compared them for both groups/periods. We look at differences between actor types within these networks and focus on network authorities and centralization patterns. Furthermore, we conduct a quantitative content analysis of tweets mentioning leading candidates. Using a random selection of these tweets (n=800), we will clarify how MPs and journalists evaluate and comment on campaign leaders in their tweets. We expect that political commentators will differ widely from political actors in terms of direct support. However, Twitter constitutes a space where boundaries are blurry and even journalists take on a more activist stance or exhibit snarky comments (Mourão 2015). By considering both groups and different phases in the election campaign communication on Twitter, our study contributes to the comprehension of dynamics. Preliminary Results Overall, the groups sent nearly 220,000 tweets (including retweets) across all periods. During the pre-campaign period (76 days of tracking), 383 political journalists (ntweets=49,676) contributed tweets and 466 MPs (ntweets=76,029). 521 MPs and 364 journalists posted tweets in the campaign period. MPs engaged a lot more in tweeting around the election (ntweets=54,345), whereas journalists only slightly increased their per day activity in the shorter second period (ntweets=39,401, only 49 days). Hyperactive accounts partially dominate both groups. An inspection of hubs and authorities in the four @mention networks computed for both groups and both periods exhibits that journalists and MPs tend to choose different authorities and actor types, especially in the pre-campaign period. Further differences are highlighted through a hashtag analysis. Even in election times, the most visible hashtag in BPK journalists’ tweets was #afghanistan. However, if the number of different journalists is considered, #btw21 is the most prevalent hashtag in this group. Further differences emerge through the comparison of subgroups. Results from our quantitative coding of @mentioning leading candidates will be presented at #AoIR22. We will especially highlight evaluations. References Borra, E. & Rieder, B. (2014). Programmed method: developing a toolset for capturing and analyzing tweets. Aslib Journal of Information Management 66(3): 262–278. https://doi.org/10.1108/AJIM-09-2013-0094 Broersma, M. & Graham, T. (2015). Tipping the Balance of Power. In A. Bruns, G. Enli, E. Skogerbo, A. Larsson & C. Christensen (eds.), The Routledge Companion to Social Media and Politics (p. 89–103). Routledge. Chadwick, A. (2017). The Hybrid Media System. Oxford University Press. Corchia, L. (2019). Political communication in Social Networks Election campaigns and digital data analysis. Rivista Trimestrale 2/19. https://doi.org/10.32049/RTSA.2019.2.04 Fitzpatrick, J. & Jöst, P. (2021). Der webbasierte Bundestagswahlkampf 2021. FJSB 34(3): 417–425. https://doi.org/10.1515/fjsb-2021-0039 Holtz-Bacha, C. (2019). Bundestagswahl 2017. In C. Holtz-Bacha (ed.), Die (Massen-) Medien im Wahlkampf (p. 1–26). Springer. Jungherr, A. (2015). Twitter use in election campaigns. Journal of Information Technology & Politics 13(1): 72–91. https://doi.org/10.1080/19331681.2015.1132401 Larsson, A. O. (2017). Going viral? Comparing parties on social media during the 2014 Swedish election. Convergence 23(2): 117–131. https://doi.org/10.1177/1354856515577891 https://doi.org/10.1108/AJIM-09-2013-0094 https://doi.org/10.32049/RTSA.2019.2.04 https://doi.org/10.1515/fjsb-2021-0039 https://doi.org/10.1080/19331681.2015.1132401 https://doi.org/10.1177/1354856515577891 Leidecker-Sandmann, M. & Wilke, J. (2019). Aus dem Rahmen fallend oder eher „middle of the road“? In C. Holtz-Bacha (ed.), Die (Massen-)Medien im Wahlkampf (p. 209–242). Springer. Molyneux, L. & Mourão, R. (2019). Political Journalists’ Normalization of Twitter. Journalism Studies 20(2): 248–266. https://doi.org/10.1080/1461670x.2017.1370978 Mourão, R. (2015). The Boys on the Timeline. Journalism 16(8): 1107–1123. https://doi.org/10.1177/1464884914552268 Nuernbergk, C. & Conrad, J. (2016). Conversations and Campaign Dynamics in a Hybrid Media Environment. SM+S 2(1): 1–14. https://doi.org/10.1177/2056305116628888 Vowe, G. (2021). Wie digitalisiert war der Bundestagswahlkampf 2021? MIP 27(2): 215–229. https://doi.org/10.24338/mip-2021215-229 https://doi.org/10.1080/1461670x.2017.1370978 https://doi.org/10.1177/1464884914552268 https://doi.org/10.1177/2056305116628888 https://doi.org/10.24338/mip-2021215-229 Paper 2: POLITICAL ADVERTISEMENT ON FACEBOOK IN THE LEAD-UP TO THE 2021 GERMAN FEDERAL ELECTIONS Nicola Righetti University of Vienna Fabio Giglietto University of Urbino Carlo Bo Azade Kakavand University of Vienna Aytalina Kulichkina University of Vienna Giada Marino University of Sassari Massimo Terenzi University of Urbino Carlo Bo Context and Relevance of the Study The 2021 German federal election held on 26 September 2021 was characterized by unprecedented political uncertainty. Angela Merkel, who has dominated German politics for 16 years as chancellor, did not run for office again. The two major parliamentary parties that lead the government in the “grand coalition,” the SPD and the CDU/CSU or their candidates, were facing several scandals, leading to fluctuating polls. But also, the Greens, who profited from a timely and smooth nomination of their candidate, faced criticism for incorrectly stating extra income and inaccuracies in the candidate’s CV. Still, with an agenda of massive public investment to launch a “social-ecological transformation,” they had a chance to lead a national government for the first time in their 40-year history (Baasner & Seidendorf, 2021). Starting from a different ideological perspective, the far-right party Alternative für Deutschland (AfD), founded in 2013, established itself in national and local politics. In the national elections in the same year, they reached 4.7% of the votes, almost passing the 5 percent threshold. In 2017, the party came third with 12.6% of the votes. The 2021 national election was moreover taking place in the extraordinary context of the COVID-19 pandemic. Along with the transformation in political communication that put digital media at the forefront of electoral campaigns, the social distancing measures have hindered non-mediated forms of campaigning and further increased the importance of long-distance traditional and especially digital communication. Social media also paves the way to a range of information operations aimed at manipulating the traditional media and public opinion (Marwick & Lewis, 2017). It empowers native and foreign political actors to run micro-targeted online advertisements to influence specific cohorts with distinct messages (Hegelich & Serrano, 2019). Microtargeting strategies on social media can potentially spread particular messages tailored to explicit categories of citizens, potentially distorting the perception of the issues at stake, giving a partial knowledge of the parties’ programs, and increasing the divisions and polarization of the civil society. As part of a broader study, we analyze paid social media communication from political candidates, parties, and other social media users, in the lead-up to the 2021 German federal election. We document the investment in Facebook advertising of the main parties and their targeting strategies. Leading Research Question What are a) costs and volume of advertising per party, b) the demographic characteristics of the targets, and c) the evidence on micro-targeted political advertising? How have they changed compared to what was found by previous research conducted in the context of the 2019 European election in Germany (Hegelich & Serrano, 2019)? Method The data collection was carried out through the Facebook Ad Library API. The initial datasets consisted of 20,703 advertisements totaling more than 475,000,000 impressions, published from 16/08/202 to 26/09/2021 from 622 funding entities. The focus of the analysis was restricted to 13,707 advertisements totaling more than 413,000,000 impressions, which were sponsored by 233 funding entities directly connected to the seven main political parties (i.e., national and regional pages of the parties). To explore possible cases of microtargeting in more detail, we looked for instances of “extreme” types of targeting, that is, advertisements 100% targeted to a certain gender or age class. To this aim, we used the Gini coefficient, a popular measure of statistical dispersion, especially used for analyzing inequality or concentration. Results According to the data provided by the Facebook Ad Library API, the seven main parties running for the Federal Elections are estimated to have spent between 2,454,700 EUR and 4,191,493 EUR. As in 2019, the AfD reached an exceptionally high engagement on Facebook (Serrano et al., 2019), but Die Grünen, instead of the CDU, led the standings of the Facebook advertisement investment in 2021. Nonetheless, they were both overtaken in the overall number of ad impressions by the FDP, who strategically spent less on a higher number of advertisements. Considering the area of microtargeting, our findings show that the content of some advertisements was exclusively targeted to women or young generations. They, however, represented just a modest part of the total number of advertisements run by parties and candidates. These results might suggest that micro-targeting strategies are not a very common tool of German parties. However, firm conclusions can hardly be reached due to the limitations of available data. Indeed, Facebook provides advertisers with several sophisticated targeting options that can be effectively used for micro-targeting, but the employed targeting (or micro-targeting) strategies cannot be inferred from the data made available. References Baasner, F., Seidendorf, S. (2021). A year of electoral uncertainty. German turns the page on Merkel. European issues n. 593 (Fondation Robert Schuman. The Research and Studies Centre on Europe). https://www.robert-schuman.eu/en/doc/questions-d-europe/qe-593-en.pdf Hegelich, S., Serrano, J. C. M. (2019). Microtargeting in Deutschland bei der Europawahl 2019. Landesanstalt für Medien NRW 2019. https://www.medienanstalt-nrw.de/fileadmin/user_upload/lfm-nrw/Foerderung/For schung/Dateien_Forschung/Studie_Microtargeting_DeutschlandEuropawahl2019 _Hegelich.pdf. Marwick, A., & Lewis, R. (2017). Media Manipulation and Disinformation Online. Data & Society. https://datasociety.net/pubs/oh/DataAndSociety_MediaManipulationAndDisinform ationOnline.pdf Serrano, J. C. M., Shahrezaye, M., Papakyriakopoulos, O., & Hegelich, S. (2019, July). The Rise of Germany's AfD: A Social Media Analysis. In Proceedings of the 10th international conference on social media and society (pp. 214-223) https://www.robert-schuman.eu/en/doc/questions-d-europe/qe-593-en.pdf https://www.medienanstalt-nrw.de/fileadmin/user_upload/lfm-nrw/Foerderung/Forschung/Dateien_Forschung/Studie_Microtargeting_DeutschlandEuropawahl2019_Hegelich.pdf https://www.medienanstalt-nrw.de/fileadmin/user_upload/lfm-nrw/Foerderung/Forschung/Dateien_Forschung/Studie_Microtargeting_DeutschlandEuropawahl2019_Hegelich.pdf https://www.medienanstalt-nrw.de/fileadmin/user_upload/lfm-nrw/Foerderung/Forschung/Dateien_Forschung/Studie_Microtargeting_DeutschlandEuropawahl2019_Hegelich.pdf https://datasociety.net/pubs/oh/DataAndSociety_MediaManipulationAndDisinformationOnline.pdf https://datasociety.net/pubs/oh/DataAndSociety_MediaManipulationAndDisinformationOnline.pdf Paper 3: ELECTIONEERING IN PANDEMIC TIMES: THE 2022 AUSTRALIAN FEDERAL ELECTION ON FACEBOOK AND TWITTER Axel Bruns Digital Media Research Centre, Queensland University of Technology Daniel Angus Digital Media Research Centre, Queensland University of Technology Timothy Graham Digital Media Research Centre, Queensland University of Technology Ehsan Dehghan Digital Media Research Centre, Queensland University of Technology Nadia Jude Digital Media Research Centre, Queensland University of Technology Phoebe Matich Digital Media Research Centre, Queensland University of Technology Introduction The 2022 Australian federal election campaign, between March and May 2022, takes place in the immediate aftermath of the COVID-19 pandemic – a period of time during which most Australian states and territories experienced severe disruptions from sometimes lengthy lockdowns; internal and external borders were closed to all but essential travel; and significant disagreements unfolded between state and federal leaders about appropriate public health, economic, and civil liberties responses to the immediate pandemic threat itself, to its impact on the economy, and to the spread of mis- and disinformation seeking to exploit the situation for hyperpartisan political benefit. The conservative federal government by the Coalition of Liberal and National Parties under the leadership of Prime Minister Scott Morrison, in particular, has been widely criticised for its lack of forward planning, its misdirected financial support that benefitted major corporations rather that citizens, and its politicisation of policy differences between state and federal leaders (e.g. Glenday, 2022). Meanwhile, overshadowed by the public attention directed to state and territory leaders during the pandemic, the oppositional Australian Labor Party has struggled at federal level to clearly present an alternative vision for the country, with opinion polls still showing considerable uncertainty about the leadership credentials of opposition leader Anthony Albanese. Such disenchantment with both major party blocs is exploited, in turn, by a wave of broadly centrist independent candidates seeking to win electorates previously held by conservatives and unlikely to elect Labor politicians; in addition, the populist United Australia Party under the leadership of controversial mining billionaire Clive Palmer has already begun an aggressive billboard, broadcast, SMS, and online advertising campaign that seeks to disrupt the conventional party landscape and is actively distributing COVID-19 disinformation (Taylor & Karp, 2021). Tendentious electioneering and outright disinformation, related to COVID-19 as well as to other major issues, are also likely to feature in the major parties’ campaigns, however: in past elections, the Labor Party executed a successful ‘Mediscare’ campaign, worrying voters about supposed Coalition plans to wind back universal healthcare in Australia (Hunter, 2016); the Coalition won the 2019 election in part as a result of its ‘Death Tax’ campaign, misrepresenting Labor’s plans to reduce tax benefits for rich retirees (Emerson & Weatherill, 2019). Such campaigns are likely to find fertile ground in a fractious and frustrated electorate that is already affected by substantial volumes of COVID-19 mis- and disinformation. Approach Building on the methodology established in our studies of Australian federal elections in 2013, 2016, and 2019, this work-in-progress paper presents a first analysis of social media campaigning during the 2022 Australian federal election. For this we draw on our established approach to analysing Twitter campaigning (as utilised for our studies of the 2013, 2016, and 2019 campaigns; Bruns, 2017; Bruns & Moon, 2018; Bruns et al., 2021) and on our translation of that approach to the analysis of campaigning via candidate pages on Facebook (as developed for the 2020 Queensland state election; Bruns & Angus, 2020). As part of an international collaboration to identify political candidates on social media platforms that has already produced a dataset of election candidates on Twitter for the 2021 federal election in Germany (Sältzer, 2021), we identify the Twitter accounts and Facebook pages of all Australian federal election candidates, and use the Twitter API and the Facebook data tool CrowdTangle to capture all posts by these accounts and pages, and all tweets directed at the candidate accounts on Twitter as well as interactions around the candidate pages on Facebook. We capture these throughout the election campaign, from the official issuing of the electoral writs to the election day. As in our previous election analyses, we draw on these datasets to produce a number of insights; as the 2022 election has yet to take place, we use examples from past elections to illustrate these here. First, we investigate the overall distribution of engagement with the different parties and their candidates. Such engagement commonly centres on the Liberal and Labor Parties as the most prominent Australian political parties, and here especially on their respective candidates for the Prime Ministership (see fig. 1 as an example of engagement with party candidates on Twitter during the 2019 election), but our longitudinal analysis of data from the past three elections shows that differences across election cycles point to the relative salience of the parties’ electoral messaging (Bruns et al., 2021). Fig. 1: Engagement on Twitter with candidates in the 2019 Australian federal election Second, we track such engagement across the campaign period. Here, we examine especially the utilisation of specific platform affordances (@mentions, retweets, quote tweets on Twitter; comments, shares, and reactions on Facebook) over time, in order to identify key campaign moments (leaders’ debates, policy releases, controversies) and determine the popular reaction they generated (see fig. 2 as an example of the dynamics of Facebook reaction sentiment for the major parties during one week in the 2020 Queensland state election). We further combine this with the computational extraction of major themes from the content gathered from both platforms, in order to correlate campaigning themes and voter engagement. Fig. 2: Positive (love, care, haha, wow) and negative (sad, angry) Facebook reactions to candidate posts during one week in the 2020 Queensland state election Finally, we also draw on a state-of-the-art detection toolkit to identify cases of coordinated behaviour in the dataset: these may include behaviours like coordinated posting, coordinated link-sharing, coordinated post sharing on Facebook or retweeting on Twitter, or coordinated commenting. Some such behaviours, in turn, may represent standard practice in social media campaigning (for instance as several party candidates post the same talking points, campaign memes, or news articles at the same time), while others may point to more covert and problematic activities (as party operatives or other actors engage in astroturfing or sockpuppeting in order to artificially inflate the visibility of specific topics). We engage in close reading and forensic analysis to investigate and assess such cases of coordinated behaviour. This paper presents the insights emerging from these analyses, in the turbulent political aftermath of the COVID-19 pandemic. In this panel it is further complemented by a paper that specifically investigates political advertising practices on Facebook during the election. In combination, the papers provide a rich and timely analysis of social media campaigning and engagement during the 2022 Australian federal election. References Bruns, A. (2017). Tweeting to Save the Furniture: The 2013 Australian Election Campaign on Twitter. Media International Australia, 162, 49–64. https://doi.org/10.1177/1329878X16669001 Bruns, A., & Angus, D. (2020). 2020 Queensland State Election: Week 1-4 Update. QUT Digital Media Research Centre. https://research.qut.edu.au/dmrc/2020/10/09/2020-queensland-state-election-week-1- update/, https://research.qut.edu.au/dmrc/2020/10/16/2020-queensland-state-election- week-2-update/, https://research.qut.edu.au/dmrc/2020/10/23/2020-queensland-state- election-week-3-update/, https://research.qut.edu.au/dmrc/2020/10/30/2020- queensland-state-election-week-4-update/ Bruns, A., Angus, D., & Graham, T. (2021). Twitter Campaigning Strategies in Australian Federal Elections 2013–2019. Social Media + Society, 7(4). https://doi.org/10.1177/20563051211063462 Bruns, A., & Moon, B. (2018). Social Media in Australian Federal Elections: Comparing the 2013 and 2016 Campaigns. Journalism & Mass Communication Quarterly, 95(2), 425–448. https://doi.org/10.1177/1077699018766505 Emerson, C., & Weatherill, J. (2019). Review of Labor’s 2019 Federal Election Campaign. Australian Labor Party. https://alp.org.au/media/2043/alp-campaign-review- 2019.pdf Glenday, J. 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(2021). Twitter Accounts of Candidates in the German Federal Election 2021 (GLES). Cologne: GESIS Data Archive. ZA7721. Data file version 2.0.0. https://doi.org/10.4232/1.13790 Taylor, J., & Karp, P. (2021, 7 Sep.). Clive Palmer and Craig Kelly Using Spam Text Messages to Capture Rightwing Vote ahead of Election, Expert Says. The Guardian. https://www.theguardian.com/australia-news/2021/sep/08/clive-palmer-and-craig-kelly- using-spam-text-messages-to-capture-rightwing-vote-ahead-of-election-expert-says http://www.smh.com.au/federal-politics/federal-election-2016/australian-federal-election-2016-malcolm-turnbulltakes-full-responsibility-for-campaign-20160705-gpyx9z.html http://www.smh.com.au/federal-politics/federal-election-2016/australian-federal-election-2016-malcolm-turnbulltakes-full-responsibility-for-campaign-20160705-gpyx9z.html https://doi.org/10.4232/1.13790 https://www.theguardian.com/australia-news/2021/sep/08/clive-palmer-and-craig-kelly-using-spam-text-messages-to-capture-rightwing-vote-ahead-of-election-expert-says https://www.theguardian.com/australia-news/2021/sep/08/clive-palmer-and-craig-kelly-using-spam-text-messages-to-capture-rightwing-vote-ahead-of-election-expert-says Paper 4: PLATFORM-BASED POLITICAL ADVERTISING: NEW APPROACHES FOR ENHANCING PLATFORM OBSERVABILITY Daniel Angus Digital Media Research Centre, Queensland University of Technology Mark Andrejevic School of Media, Film, and Journalism, Monash University Bronwyn Carlson Department of Indigenous Studies, Macquarie University Axel Bruns Digital Media Research Centre, Queensland University of Technology Abdul Obeid Digital Media Research Centre, Queensland University of Technology Philip Mai Social Media Lab, Ryerson University Anatoliy Gruzd Social Media Lab, Ryerson University Introduction Platform-based political advertising is emerging as a key focal point of modern elections. It has also fast become a new regulatory battleground, as governments and citizenries around the globe grapple with the consequences of this new campaign practice (Kreiss & Mcgregor, 2019). Key concerns relate to the ability to algorithmically target hyper-partisan and false information, and with the lack of transparency from political actors and the palatforms themselves, regarding the advertisements placed, money spent, and ultimately who is consuming these advertisements (Dommett & Power, 2019). The Cambridge Analytica scandal revealed the susceptibility of platform-based political advertising to exploitation, particularly in relation to the UK’s Brexit referendum and Donald Trump’s 2016 election (Cadwalladr, 2018). In the wake of this scandal – and due in no small part to significant sustained pressure from academics, journalists, civil society groups, and eventually governments – the major platforms have been forced to curtail certain advertising practices, and implement a range of political advertising transparency initiatives. A key feature of these initiatives is the provision of new digital tools, often in the form of transparency ‘dashboards’. These platform-provided dashboards offer basic information as to the ads that are or have recently been run, who is sponsoring these ads, and basic aggregated statistics as to the reach and audience of the ads. While welcome, the dashboards provided by large platforms like Meta and Google stop short of full transparency (Edelson et al. 2019). As one example, Facebook and Instagram ads are readily targeted to highly specific geolocations (down to individual suburb/postcode level) by ad buyers, however Meta’s dashboards only reveal geolocation data at an entire state level. Interest categories for ads are also heavily abstracted making it difficult to interrogate where political advertising may be engaging in racial, gendered, economic, religious, or other harmful forms of discrimination. More so, we are left to trust that information provided by the platforms is accurate, given there is no independent oversight or verification of this data. Due to the fundamental limitations of platform-provided transparency tools, researchers are turning to other techniques to provide much needed platform observability (Rieder & Hofmann, 2020). In some cases, this involves the augmentation of transparency dashboards to turn them into more easily searchable ad archives, with additional statistics and information visualisation. In other cases researchers are side stepping platform-provided approaches completely using data donation plugins that enrol platform users to contribute any ads encountered while browsing these platforms into platform-independent archives (ProPublica, 2020). New Approaches for Advertising Accountability In this paper we outline a suite of digital methods developed to study platform-based political advertising, and ultimately enhance platform observability and accountability. We focus on a study of political advertising that will be conducted throughout the upcoming Australian Federal Election campaign, due to take place no later than May 2022. The data collection methods that have already been developed and deployed in the lead up to this national election range from data gathering techniques that utilise existing platform-provided ad transparency APIs (PoliDashboard: https://global.polidashboard.com/), through to citizen-science data donation approaches (Australian Ad Observatory: https://www.admscentre.org.au/adobservatory/). Additionally, we have also developed a range of computational methods to support both quantitative and qualitative data analysis. The first tool, PoliDashboard, was originally developed by the Social Media Lab, Ryerson University, as part of an international election transparency initiative. PoliDashboard has been extended in partnership with members of our research team for the Australian context. The tool interfaces with the existing Meta and Google ad transparency libraries, but offers additional archival, ranking, search, data aggregation, and visualisation abilities (see Figure 1). https://global.polidashboard.com/ https://www.admscentre.org.au/adobservatory/ Figure 1: Screenshots of the PoliDashboard (credit: Social Media Lab, Ryerson University) The second tool, the Australian Ad Observatory (Burgess et al., 2021) extends the work of the Ad Observatory developed by researchers at NYU, which itself extends the ProPublica Political Ad Collector (ProPublica, 2020). The Observatory relies on the use of a browser plugin, installed by volunteer members of the Australian public on their personal computers. The browser plugin detects any sponsored posts that participants encounter in their Facebook news feeds during regular use of Facebook through their browser. Once detected by the plugin, ads are anonymously sent to a central server along with additional demographic data from the participants (if they have chosen to provide such information). The browser plugin works without requiring any manual intervention from the participants, who can also review their own personal catalogue of ads encountered at any time via the tool. In addition to the collection of political ads via the above data collection tools, we have implemented a range of new critical data analytic approaches to assist in analysis of campaign materials (Burgess et al., 2021). These approaches encompass optical character recognition (OCR), logo and object detection, and visual and text-based content analysis support, including topic modelling and machine vision. The approaches serve to assist in the discovery of specific political messaging, analyse campaign spending and reach, and examine visual presentation and communication within ads (see Fig 2). Figure 2: Screenshot of the Australian Ad Observatory researcher dashboard. While the approaches are developed as a general and highly versatile toolset for the study of platform-based political advertising materials, a specific focus for our team is on the detection and analysis of false or misleading advertising materials, and to also understand the experiences of Indigenous users of these platforms given existing concerns regarding discriminatory algorithmic advertising practices (Andrejevic et al., 2022). We will highlight specific examples encountered, and other general findings as part of our analysis, in addition to guidance on how these techniques can be adopted in future studies of political and non-political platform-based advertising. References Andrejevic, M., Fordyce, R., Li, N., & Trott. V. (2021) Unregulated and segmented dark ads on social media: consumer education and regulatory options. Retrieved from: https://apo.org.au/sites/default/files/resource-files/2021-06/apo-nid313053.pdf Andrejevic, M., Fordyce, R., Li., N, & Trott, V. in collaboration with Angus, D. & Tan, J. (forthcoming) Ad accountability online: a methodological approach, in Pink, S., M. Berg, D. Lupton, & M. Ruckenstein (forthcoming) Everyday Automation: Experiencing and Anticipating Emerging Technologies. London, NY: Routledge, pp. 213-224 Burgess, Jean, Daniel Angus, Nicholas Carah, Mark Andrejevic, Kiah Hawker, Kelly Lewis, Abdul Karim Obeid et al. "Critical simulation as hybrid digital method for exploring the data operations and vernacular cultures of visual social media platforms." (2021): https://osf.io/preprints/socarxiv/2cwsu/download. Cadwalladr C. (2018, March 18), ‘I made Steve Bannon’s psychological warfare tool’: meet the data war whistleblower, The Guardian, Retrieved from https://www.theguardian.com/news/2018/mar/17/data-war-whistleblower-christopher- wylie-faceook-nix-bannon-trump. Dommett, K., & Power, S. (2019). The political economy of Facebook advertising: Election spending, regulation and targeting online. The Political Quarterly, 90(2), 257- 265. Edelson, L., Sakhuja, S., Dey, R., & McCoy, D. (2019). An analysis of United States online political advertising transparency. arXiv preprint arXiv:1902.04385. Krafft, T. D., Gamer, M., & Zweig, K. A. (2019). What Did You See? A Study to Measure Personalization in Google’s Search Engine. EPJ Data Science, 8 (1), 1–23. https://doi.org/10.1140/epjds/s13688-019-0217-5 Kreiss, D., & Mcgregor, S.C. (2019) The “Arbiters of What Our Voters See”: Facebook and Google’s Struggle with Policy, Process, and Enforcement around Political Advertising, Political Communication, 36:4, 499-522, DOI: 10.1080/10584609.2019.1619639 Rieder, B., & Hofmann, J. (2020). Towards platform observability. Internet Policy Review, 9(4), 1-28. ProPublica. (2020). Facebook Political Ad Collector. Retrieved from: https://projects.propublica.org/facebook-ads/ https://urldefense.com/v3/__https:/apo.org.au/sites/default/files/resource-files/2021-06/apo-nid313053.pdf__;!!NVzLfOphnbDXSw!V5K65AEFDEF6pBye-fJVjwyeQs2J70RHHrX0kvoIm5uyS_QeegcGV6gPgNZqcr5-BnrpsYsa$ https://urldefense.com/v3/__https:/osf.io/preprints/socarxiv/2cwsu/download__;!!NVzLfOphnbDXSw!V5K65AEFDEF6pBye-fJVjwyeQs2J70RHHrX0kvoIm5uyS_QeegcGV6gPgNZqcr5-Bk5-dHYn$