Journal of Elections, Public Opinion and Parties ISSN: 1745-7289 (Print) 1745-7297 (Online) Journal homepage: www.tandfonline.com/journals/fbep20 Concerns about misinformation on Instagram in five countries Christian Pieter Hoffmann & Shelley Boulianne To cite this article: Christian Pieter Hoffmann & Shelley Boulianne (21 Jun 2025): Concerns about misinformation on Instagram in five countries, Journal of Elections, Public Opinion and Parties, DOI: 10.1080/17457289.2025.2514192 To link to this article: https://doi.org/10.1080/17457289.2025.2514192 © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group View supplementary material Published online: 21 Jun 2025. Submit your article to this journal Article views: 9 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=fbep20 JOURNAL OF ELECTIONS, PUBLIC OPINION AND PARTIES https://doi.org/10.1080/17457289.2025.2514192 Concerns about misinformation on Instagram in five countries Christian Pieter Hoffmann a a and Shelley Boulianne b Institute of Communication and Media Studies, University of Leipzig, Leipzig, Germany; R. Klein Chair in Communication Studies, Mount Royal University, Calgary, Canada b ABSTRACT Use of Instagram has proliferated over recent years, as have concerns about misinformation. Yet, most misinformation research has focused on Facebook and Twitter. Based on a survey of more than 4000 Instagram users from the United States, the United Kingdom, France, Canada, and Germany, this study examines general predictors of concerns about misinformation on Instagram and predictors specific to the platform’s information environment. We highlight three potential conceptual accounts of misinformation concerns: fears of being misled due to (incidental) exposure to misinformation, exposure to politically cross-cutting content, and third-person effects. We find that seeing political content on Instagram (from one’s network or other sources) positively and significantly relates to concerns about misinformation, while the political heterogeneity of one’s network does not. Neither political interest nor ideology relate to concerns over misinformation on Instagram, but users’ perceived ability to identify misinformation does. These findings indicate that concerns about misinformation on Instagram are largely related to a third-person effect. We examine if findings replicate across all five countries. Concerns about misinformation are important to understand as they relate to increased vigilance and thus, reduced susceptibility to misinformation, to institutional trust, and to support for government interventions to combat misinformation. ARTICLE HISTORY Received 27 February 2024; Accepted 23 January 2025 KEYWORDS Instagram; social networks; misinformation; concerns; political information; public opinion; cross-national; third-person effect Introduction Across the globe, people are concerned about misinformation shared on social media (Newman et al. 2024), independent of its actual prevalence. Mis­ information can be defined as false or misleading information (Altay et al. CONTACT Christian Pieter Hoffmann christian.hoffmann@uni-leipzig.de Institute of Communi­ cation and Media Studies, University of Leipzig, Nikolaistrasse 27-29, 04109 Leipzig, Germany Supplemental data for this article can be accessed http://doi.org/10.1080/17457289.2025.2514192. © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. 2 C. P. HOFFMANN AND S. BOULIANNE 2023). The Digital News Report 2024 found that the share of those concerned about what is real or fake when it comes to news online has risen to 59% across all surveyed markets (Newman et al. 2024). Concerns over misinforma­ tion are associated with a sense of skepticism or mistrust towards news (Hoes et al. 2022; van der Meer, Hameleers, and Ohme 2023; Van Duyn and Collier 2019). This is worrying as research indicates that exposure to online misinfor­ mation tends to be limited and users overwhelmingly consume news from reliable sources (Allen et al. 2020; Eady et al. 2023; Moore, Dahlke, and Hancock 2023). If concerns over misinformation shake institutional trust, they may ultimately weaken the public’s resilience vis-à-vis actual disinforma­ tion campaigns (Humprecht, Esser, and Van Aelst 2020). Therefore, it is impor­ tant to understand the context and correlates of concerns about misinformation (van Doorn 2023). Within the scholarship on misinformation on social media, research has focused on Facebook and Twitter, leaving questions about other platforms. Understanding user perceptions of misinformation on these other platforms is important given the splintering of users across platforms and their distinct features and use dynamics (cf., Boulianne, Hoffmann, and Bossetta 2024). In this paper, we examine concerns about misinformation on Instagram. The use of Instagram has grown rapidly over recent years (Newman et al. 2023). According to the Digital News Report, across 46 surveyed markets, 44% of respondents used Instagram in 2023. Instagram is especially popular among young users: 61% of adults aged 18–24 use Instagram (Newman et al. 2023). While not all Instagram users seek political information or news on the platform, globally, about 15% do (Newman et al. 2024), which is a larger than the percentage using Twitter/X. We follow up on studies showing that the correlation between Instagram use and perceived exposure to misinformation is as large, if not larger, than in the context of Facebook use (Blanco-Herrero, Amores, and Sánchez-Holgado 2021; Neyazi et al. 2022). Instagram is a site focused on visual content. Research on visual misinformation, however, is still in its infancy (Weikmann and Lecheler 2023). Recent technological advances in the domain of genera­ tive AI have fanned interest in visual mis – and disinformation (Simon, Altay, and Mercier 2023; Vaccari and Chadwick 2020). In addition, there is some evi­ dence that influencers (such as celebrities) could be especially important for the flow of political information on Instagram (Newman et al. 2024). At the same time, initial studies indicate that ties among users may play a more pro­ nounced role in the spread of misinformation (Klüser and Hoes 2024; Lotto et al. 2022; Massey et al. 2020). Based on a survey of more than 4000 Instagram users from the United States, the United Kingdom, France, Canada, and Germany, this study explores both general predictors of concerns about misinformation on Insta­ gram and predictors specific to the platform’s information environment. We JOURNAL OF ELECTIONS, PUBLIC OPINION AND PARTIES 3 use a similar case method (Seawright and Gerring 2008), examining countries that have similar macro-level characteristics. Among the general predictors are users’ political interest, perceived ability to identify misinformation, and per­ ceived exposure to misinformation on social media. To examine the platformspecific predictors, we highlight how users are exposed to news and political information on Instagram. We analyze the relationship between social network size, political network heterogeneity, network’s political posting behavior, and concerns about misinformation. Examining these variables allows for an exploration of distinct theoretical accounts for misinformation concerns: rational concerns due to (incidental) exposure to misinformation, exposure to politically cross-cutting content, and third-person effects. Concerns about misinformation are important to understand for several reasons. At the micro-level, concerns about misinformation may increase vig­ ilance and could thus render individuals less susceptible to misinformation (Lewandowsky and Van Der Linden 2021). At the same time, concerns about misinformation may induce a generalized sense of mistrust towards online information and thereby lower trust in quality information (cf., Hamel­ eers, Brosius, and de Vreese 2022; Ternovski, Kalla, and Aronow 2022; van der Meer, Hameleers, and Ohme 2023). Harris and colleagues (2024) find that individuals concerned about misinformation rely more heavily on politically aligned news sources. Interventions aiming at combating misinformation must therefore accurately assess the context and correlates of concerns over misinformation to avoid deleterious downstream effects (Tay et al. 2023; van Doorn 2023). Altay and Acerbi (2023) report that concerns about misinformation correlates with “liking” and sharing alarmist narratives about misinformation. Such narratives, in turn, are likely to undermine trust in institutions and shore up support for restrictive policy interventions (cf., Jungherr and Rauchfleisch 2024). Misinformation on Instagram The research on misinformation on Instagram is limited and heterogeneous. In a study of UK citizens, Chadwick, Vaccari, and Kaiser (2022) found that sharing misinformation correlates with the use of Instagram for news. However, a recent study of Mexican citizens found no relationship between Instagram use and belief in political misinformation (Valenzuela, Muñiz, and Santos 2022). Blanco-Herrero, Amores, and Sánchez-Holgado (2021) report that a sizeable share of Spanish citizens report encountering misinformation on Instagram. Neyazi et al. (2022) showed that the use of Instagram in the context of national elections in Indonesia was positively related to selfreported misinformation exposure. So the available evidence indicates that users believe that they encounter misinformation on Instagram, which may induce concerns about misinformation. 4 C. P. HOFFMANN AND S. BOULIANNE There is some initial evidence that the platform architecture (Bossetta 2018) plays a role in misinformation on Instagram. Massey et al. (2020) focus on misinformation about the HPV vaccine. They find that misinforma­ tion on Instagram is multimodal, encompassing visual and textual elements (cf., Tuters and Willaert 2022). Hong et al. (2023), studying anti-Asian misinfor­ mation in the context of the COVID-19 pandemic, find that Instagram focused on hashtags in their content moderation efforts. Hashtags are used to create topic networks. Beyond this study, however, the network effects of misinfor­ mation on Instagram are largely unexplored. In particular, little is known about how one’s social network (size of network, network activities) on Insta­ gram influences exposure to and concerns about Instagram. The 2024 Digital News Report (Newman et al. 2024) found that personalities or celebrities play a key role in how users encounter news on Instagram (cf., Swart and Broersma 2023). Mena, Barbe, and Chan-Olmsted (2020) show that endorsement by trusted parties (i.e. likes of a post by a celebrity) increases the credibility of misleading Instagram content. Yet, a recent analysis of Insta­ gram influencers by Klüser and Hoes (2024) shows that influencers very rarely spread falsehoods (just 0.003% of the examined posts). Instead, Massey et al. (2020) and Lotto et al. (2022) find that health misinformation on Instagram is mostly posted by private citizens. This content revolves around personal experiences and is thus characterized by immediacy. These findings indicate that rather than influencers, fellow users and the pol­ itical content they post play a relevant role in how misinformation spreads on Instagram. Concerns about misinformation Applying findings from public opinion research, concerns about misinforma­ tion can be defined as a subjective assessment that misinformation is a serious problem worthy of anxiety or worry due to the prevalence and/or severity of its consequences. Studies indicate that citizens are concerned about (i) the misleading effects of misinformation on themselves and (ii) fellow citizens, as well as (iii) deleterious effects on social trust and institutions (Altay 2023; Newman et al. 2024). Analyzing data from the Digital News Report from 2018 to 2023, Altay (2023) finds that concerns about misinformation have remained quite stable during that period. Older individuals, women, the more educated, and political partisans tended to be more concerned about misinformation. However, the 2024 Digital News Report reports a rise in concerns over misinformation (Newman et al. 2024). Knuutila, Neudert, and Howard (2022) find that younger individuals, especially, feel more vulner­ able to misinformation. These findings about age are relevant for the present study as Instagram is used for information primarily by younger individuals (Boulianne and Hoffmann 2022). JOURNAL OF ELECTIONS, PUBLIC OPINION AND PARTIES 5 Conceptually, there are several potential accounts of concerns over misin­ formation. First, users may encounter misinformation online (objectively or subjectively) and thus rationally become concerned about the quality of information available on the internet. The 2024 Digital News Report (Newman et al. 2024) showed that 59% of citizens surveyed in 46 markets are concerned about “what is real and what is fake” when it comes to online news. Second, when examining misinformation concerns, it is important to under­ stand what audiences perceive or categorize as misinformation. Studies of the term “fake news’ have shown that it can denote a genre of low-quality information (misleading, lacking facticity) or a politically loaded charge intended to delegitimize (Egelhofer and Lecheler 2019). Individuals tend to qualify content as “misinformation” that is politically cross-cutting (Edgerly et al. 2020; Tsang 2022). As a result, citizens believe the respective political outgroup spreads more misinformation (Hameleers and Brosius 2022). Third, there is strong evidence of a third-person effect in concerns about misinformation, as citizens are more worried about others being misled than being misled themselves (Altay and Acerbi 2023). Nisbet, Mortenson, and Li (2021) found that such a third-person effect reduces satisfaction with democracy, especially among left-leaning citizens. We derive several hypotheses on predictors of concerns about misinforma­ tion. First, we propose that perceived exposure to misinformation on social media will predict concerns about misinformation on Instagram. In a crossnational survey, Knuutila, Neudert, and Howard (2022) find that concerns about misinformation may be unrelated to the actual level of misinformation (here: assessed by personal risk of exposure). Vegetti and Mancosu (2025) find that predictors of perceived misinformation exposure and misinformation concerns differ. As noted above, individuals apply diverging standards when subjectively categorizing content as misinformation. Actual and per­ ceived levels of misinformation can thus deviate. Still, perceived exposure to misinformation has been shown to reduce trust in news (Hoes et al. 2022) and political institutions (Jones-Jang, Kim, and Kenski 2021), induce uncertainty (Vaccari and Chadwick 2020), and is likely to positively relate to concerns about the effects of misinformation. H1: Encountering perceived misinformation on social media is positively related to concerns about misinformation on Instagram. Second, we propose that politically interested individuals will be more con­ cerned about misinformation, as they will pay more attention to elite and media discourse about misinformation (Hoes et al. 2022; Van Duyn and Collier 2019) and will be more politically engaged, and thus more likely to encounter misinformation, and/or politically cross-cutting content. Political interest predicts following news organizations and political actors on 6 C. P. HOFFMANN AND S. BOULIANNE Instagram (Boulianne and Hoffmann 2024a). Koc-Michalska et al. (2020) find that political uses of social media predict perceived exposure to misinforma­ tion. Altay (2023) argues that engagement with news content on social media increases concerns about misinformation. H2: Political interest is positively related to concerns about misinformation on Instagram. Third, we propose that those who believe in their ability to identify misin­ formation will be more concerned about it, rather than less. This hypothesis relates to the aforementioned third-person effect, as citizens have been shown to assume that they, themselves, would be able to detect misinforma­ tion while fearing that others might be misled (Altay and Acerbi 2023; Nisbet, Mortenson, and Li 2021). Individuals may be overconfident in their ability to spot misinformation (Motta, Callaghan, and Sylvester 2018), yet they may still develop strong feelings about what they perceive as misinformation. H3: Perceived ability to identify misinformation is positively related to concerns about misinformation on Instagram. Finally, users who are generally more trustful of social media companies may be less concerned about misinformation on Instagram because they have faith that these companies will provide a safe information environment. A Pew Research study among US citizens (Liedke and Gottfried 2022) recently found that, while trust in local and national news organizations has declined to record lows since 2016, trust in information on social media sites has remained stable. Among citizens aged 18-29, 50% trust social media sites, 56% trust national news organizations, and 62% trust local news. This finding highlights that users may differ in whether they consider social media sites a safe or reliable platform for news. H4: Trust in social media companies is negatively related to concerns about mis­ information on Instagram. Using Instagram for political information Beyond general predictors of concerns about misinformation, some elements of Instagram’s information environment may induce misinformation con­ cerns. Not all Instagram users use the platform to access news. According to the Reuters Institute Digital News Report, 15% of all surveyed adults across 45 markets used Instagram for news “in the last week” (Newman et al. 2024). Boulianne and Hoffmann (2022) found that about 16% of Insta­ gram users in four Western countries followed a news organization. Males were more likely to do so than females, as were users under 44 and more edu­ cated users. A recent Pew study found that the share of US citizens reporting regularly getting news on Instagram increased from 28% to 34% between JOURNAL OF ELECTIONS, PUBLIC OPINION AND PARTIES 7 2020 and 2023 (Liedke and Wang 2023). Women, young users and those favoring the Democratic party were more likely to consume news on Instagram. Previous research indicates that misinformation on Instagram is most often found in the context of political content (Lotto et al. 2022). As noted above, citizens are most concerned about misinformation shared for political purposes. In particular, they worry about political (mis-)information shared by the political outgroup (Hameleers and Brosius 2022). We propose that politi­ cal uses of Instagram may correlate with misinformation exposure, and they positively relate to the salience of news quality on Instagram and thus relate to concerns about misinformation (cf., Altay 2023). H5: Exposure to political information on Instagram is positively related to con­ cerns about misinformation on Instagram. Instagram presents users with a content feed primarily based on the accounts users choose to follow (Bossetta 2018). It also employs algorithmic curation to suggest content and accounts to follow. Since few intentionally use Instagram for news, a sizeable share of news consumption on Instagram is incidental (Boczkowski, Mitchelstein, and Matassi 2018). Thorson and Wells (2016) propose that the curation of an individual’s news exposure is, to a large degree, shaped through their ties maintained on the platform. More specifi­ cally, users may choose to follow a news or political account, but they are also exposed to the content posted/shared by their “friends’ (Boulianne and Hoffmann 2024a; Thorson et al. 2021). Barnidge and Xenos (2024) find that social network size and diversity predict incidental news exposure on social media. User characteristics, such as political interest, may be mirrored by their social networks, further amplifying the likelihood of exposure to news and political content through fellow users. This study examines the role of social networks in users’ concerns about misinformation. We propose that Instagram users are more concerned about misinformation if their Instagram network frequently posts political content. Most misinformation on Instagram appears to be posted by lay users (Massey et al. 2020; Lotto et al. 2022). Having one’s network posting political information also activates third-person concerns; in particular, users may be worried about their ties’ consumption of and beliefs in misinfor­ mation. Furthermore, if users maintain large and politically heterogeneous networks on Instagram, they are more likely to be exposed to news that they may not agree with politically. Both network characteristics are expected to positively relate to the salience of news quality and thus concerns over misinformation. H6: Network posting political content on Instagram is positively related to con­ cerns about misinformation on Instagram. 8 C. P. HOFFMANN AND S. BOULIANNE Figure 1. Research model. H7a&b: Social network size (a) and political heterogeneity (b) on Instagram are positively related to concerns about misinformation on Instagram. Figure 1 presents our research model. Finally, as we examine these hypotheses in five Western countries. We use a similar case method (Seawright and Gerring 2008), choosing countries that have similar macro-level characteristics. Specifically, prior research suggests that Freedom of the Press scores predict concerns about misinformation (Altay 2023; Vegetti and Mancosu 2025). According to Reporters Without Borders (see Newman et al. 2023), these five countries have high scores on World Press Freedom Index: Canada (83.53), France (78.72), Germany (81.91), United Kingdom (78.51), and the United States (71.22). According to the Digital News Report (Newman et al. 2023), the percentage of respon­ dents who use Instagram is 36% in the United Kingdom, 35% in Canada and the United States, 34% in France, and 26% in Germany. We pose the fol­ lowing research question: RQ1: How do the predictors of concerns about misinformation on Instagram vary across the five examined countries (USA, UK, Canada, France, and Germany)? Methods This study used survey data gathered in the United States, United Kingdom, France, Canada, and Germany. Data collection occurred in early 2023 JOURNAL OF ELECTIONS, PUBLIC OPINION AND PARTIES 9 (N = 7,500, 1500 per country). Kantar administered the survey to their online panel with quotas to ensure representation of the population in each country (sex, age, education; Table 1). The project received ethics approval in accord­ ance with Canada’s Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans. The data and replication files are available at https://doi. org/10.6084/m9.figshare.27852291.v1. The analysis focused on those who reported using Instagram during the past 12 months (N = 4,182). The sample size for each country is: Canada (N = 852), the United States (N = 918), France (N = 829), Germany (N = 758), Table 1. Descriptive statistics by country. Mean Females Education (4 groups) Age Right-wing ideology Left-wing ideology See misinformation on social media (H1) Political interest (H2) USA UK FRA CA GER Total USA UK FRA CA GER Total USA UK FRA CA GER Total USA UK FRA CA GER Total USA UK FRA CA GER Total USA UK FRA CA GER Total USA UK FRA CA GER Total 49.67% 61.45% 57.30% 58.22% 58.18% 56.79% 2.16 1.93 1.87 2.04 2.16 2.03 40.50 39.20 41.93 41.07 42.21 40.95 37.05% 23.19% 28.37% 25.37% 15.56% 26.31% 13.65% 21.38% 17.67% 21.45% 19.74% 18.67% 2.80 2.66 2.45 2.77 2.31 2.61 2.75 2.61 2.41 2.47 2.87 2.62 SD Ability to identify misinformation (H3) 1.09 1.09 1.08 1.03 1.03 1.07 14.95 14.74 16.33 16.11 15.97 15.65 Trust social media companies (H4) Frequency of Instagram use (1 = never has been removed from analysis) See political content on Instagram (H5) Instagram network posts political content (H6) 0.90 0.92 1.02 0.93 0.95 0.96 0.97 0.95 0.99 1.00 0.95 0.99 Number of accounts followed (H7a) Agree with Instagram network’s political posts (H7b) USA UK FRA CA GER Total USA UK FRA CA GER Total USA UK FRA CA GER Total USA UK FRA CA GER Total USA UK FRA CA GER Total USA UK FRA CA GER Total USA UK FRA CA GER Total Mean SD 3.33 3.03 3.04 3.21 3.22 3.17 2.76 2.27 2.22 2.33 2.40 2.40 3.21 3.34 3.26 3.26 3.35 3.28 2.31 2.04 1.98 2.12 2.10 2.11 2.13 1.93 1.91 1.91 1.79 1.94 2.93 2.93 2.31 2.76 2.55 2.71 2.32 2.10 2.18 2.19 2.15 2.19 1.02 0.91 0.95 0.95 0.80 0.94 1.30 1.15 1.17 1.17 1.02 1.19 0.77 0.78 0.79 0.79 0.77 0.78 1.04 1.02 1.04 1.04 1.01 1.04 0.94 0.90 0.95 0.91 0.85 0.92 1.40 1.43 1.27 1.46 1.35 1.40 0.99 0.97 1.00 1.00 1.01 1.00 10 C. P. HOFFMANN AND S. BOULIANNE and the United Kingdom (N = 825). We do not have country-specific hypoth­ eses; the theoretical frames should hold across these five Western democra­ cies. We use the cross-national data to test the robustness of the theoretical models across countries. Based on an ordinary least squares regression model, we present marginal plots with unstandardized coefficients with 95% confidence intervals when the coefficient is significant in the pooled results and thus merits further exploration. The full regression models for each country are available in the Appendix. The dependent variable is concerns about misinformation on Instagram. The single-item question (“How serious a problem is false information or mis­ information on Instagram?”) was modeled after the one in the American National Election Study 2020, which asks about concerns about false infor­ mation on Facebook. However, we refer to Instagram and added “or misinfor­ mation.” We provided the following definition of misinformation: “By misinformation, we mean false or misleading information.” Response options were not at all, a little, moderately, very, and extremely. The UK respondents (M = 2.85, SD = 1.13) and German respondents (M = 2.95, SD = 0.99) report, on average, lower concerns about misinformation on Instagram than other countries. Respondents from France report, on average, greater concerns about misinformation on Instagram (M = 3.12, SD = 1.14). The US respondents (M = 3.07, SD = 1.21) and Canadian respondents (M = 3.03, SD = 1.17) report, on average, similar levels of concern. While an ANOVA test suggests there are significant differences; the differences are small (F-ratio = 7.02, p < .001). For H1, we asked about perceptions of exposure to misinformation on social media. Specifically, “In the past month, how often have you seen someone share misinformation on social media?” (never, rarely, from time to time, often). For H2, political interest was assessed based on responses to “How interested would you say you are in politics?” following the World Values Survey. Four response options were provided, ranging from not at all to very interested. For H3, we asked, “How well, would you say, you are able to identify misinformation when you encounter it online?” (not at all, a little, moderately, very, extremely). For H4, respondents were asked about their confidence in a series of institutions to “act in the best interests of the public” (not at all, a little, a moderate amount, a lot, a great deal). Social media companies were included in the list. We defined political content: “please think about current events in the world, news about elections, information about political figures, information about government performance, debates about public policy, and other pol­ itical issues.” For H5, we asked whether they had seen this type of content on Instagram during the past 12 months (never, rarely, from time to time, often). For H6 and H7b, we asked, “How often do your Instagram contacts (people you follow) post political content?” and “When your Instagram contacts JOURNAL OF ELECTIONS, PUBLIC OPINION AND PARTIES 11 (people you follow) post political content, how often do you agree with what they post?” (never, rarely, time to time, often). For H7a, we asked respondents about the number of accounts they followed (0–15, 16–100, 101–200, 201– 400, more than 400). Table 1 reports the descriptive statistics. Political ideology was based on a self-placement question based on a scale of left (0) to right (10) but to address the literature’s findings, we recoded this variable into left-wing and right-wing based on the lowest/highest three cat­ egories. Those who do not express any affiliation, answered “don’t know,” or selected “neither left nor right” serve as the reference group. Gender was coded as females = 1 and males = 0. Education was based on a series of cat­ egories: high school or less, some college, a bachelor’s degree, and more than a bachelor’s degree. Age was calculated as year of birth minus year of data collection. As noted, age, sex, and education are matched to the census cat­ egories for each country (see Table 1). Results Before addressing the hypotheses, Table 2 presents a Pearson’s correlation matrix. This analysis helps rule out multi-collinearity issues but also helps untangle the relationships among the key predictors. In particular, perceived exposure to misinformation on social media is correlated with self-assessed ability to identify misinformation (r = .312, p < .001), which we would expect as validation of the measures. Seeing political information on Insta­ gram (r = .294, p < .001), having friends (network) who post political content (r = .271, p < .001), and, surprisingly, agreeing with friends’ political posts (r = .231, p < .001) are correlated with perceived exposure to misinfor­ mation on social media and concerns about misinformation on Instagram. In short, the platform-specific political content variables correlate with both perceptions of misinformation and concerns about misinformation on Instagram. Turning to the regression model presented in Table 3, we find that percep­ tions of exposure to misinformation on social media are moderately posi­ tively and significantly related to concerns about misinformation on Instagram (H1, b = .14, SE = .02, p < 0.001). This coefficient is significant in all five countries (Figure 2). We do not find a significant relationship between political interest and concerns about misinformation on Instagram (H2). This null finding was repli­ cated across the five countries. Self-assessed ability to identify misinformation is moderately positively and significantly related to concerns about misinfor­ mation (H3, b = .14, SE = .02, p < 0.001). In Figure 3, we demonstrate that this relationship is consistent across four of the five countries. Germany is the exception where there is positive relationship, but it is not statistically significant. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 ***p < .001, **p < .01, *p < .05 1. Concern 1 2. See misinformation on .227*** 1 social media 3. Agree with Instagram .221*** .231*** 1 network’s political posts .168*** .189*** .318*** 1 4. Number of accounts followed 5. Instagram network posts .281*** .271*** .598*** .415*** 1 political content 6. See political content on .256*** .294*** .452*** .384*** .556*** 1 Instagram 7. Trust social media .187*** .142*** .265*** .228*** .366*** .329*** 1 companies 8. Ability to identify .224*** .312*** .226*** .144*** .216*** .208*** .208*** 1 misinformation 9. Political interest .152*** .191*** .311*** .050** .318*** .280*** .269*** .328*** 1 10. Frequency of Instagram .104*** .099*** .217*** .424*** .219*** .319*** .084*** .087*** −.028 1 use 11. Left-wing −.007 .085*** .097*** −.007 −.018 .003 −.082*** .063*** .140*** .004 1 12. Right-wing .100*** .063*** .168*** .080*** .243*** .189*** .255*** .106*** .228*** −.017 −.286*** 1 13. Age −.112*** −.109*** −.161*** −.438*** −.232*** −.246*** −.176*** −.023 .160*** −.256*** .045** −.034* 1 14. Education .100*** .059*** .107*** .120*** .125*** .126*** .143*** .190*** .228*** .027 .028 .100*** .001 1 .048** −.080*** −.064*** −.146*** −.169*** −.227*** .104*** .015 −.159*** −.104*** −.125*** 15. Females −.048** −.055*** −.052** Table 2. Correlation matrix. 12 C. P. HOFFMANN AND S. BOULIANNE JOURNAL OF ELECTIONS, PUBLIC OPINION AND PARTIES 13 Table 3. Concerns about misinformation on Instagram. Females Education Age Left-wing Right-wing Frequency of Instagram use See misinformation on social media (H1) Political interest (H2) Ability to identify misinformation (H3) Trust social media companies (H4) See political content on Instagram (H5) Instagram network posts political content (H6) Number of accounts followed (H7a) Agree with Instagram network’s political posts (H7b) United States France Canada Germany b SE Beta p 0.01 0.04 −0.002 −0.06 0.002 0.001 0.14 0.02 0.14 0.05 0.09 0.15 0.02 0.03 0.05 0.31 0.13 0.12 0.03 0.02 0.001 0.05 0.04 0.02 0.02 0.02 0.02 0.02 0.02 0.03 0.02 0.02 0.05 0.05 0.05 0.05 0.006 0.037 −0.032 −0.022 0.001 0.001 0.117 0.018 0.117 0.055 0.079 0.123 0.020 0.027 0.018 0.110 0.046 0.040 0.690 0.015 0.060 0.167 0.966 0.959 <0.001 0.325 <0.001 0.001 <0.001 <0.001 0.291 0.151 0.348 <0.001 0.013 0.031 Males, moderates/no affiliation, and respondents from the UK are the reference groups for the above model. The r-squared is.143, with a valid sample size of 4,173. Figure 2. Perceived exposure to misinformation on social media and concerns about misinformation by country (H1). Note: Unstandardized coefficients with 95% confidence intervals for an OLS regression model. Respondents who report trust in social media companies express higher levels of concern, contrary to our hypothesis (H4, b = .05, SE = .02, p = 0.001). The relationship is small and does not replicate across the countries (Figure 4). In particular, the hypothesis is supported in Germany, where there is a significant negative relationship between trust in social media com­ panies and levels of concern. Turning to the variables specific to the Instagram’s information environ­ ment, respondents who report seeing political information on Instagram 14 C. P. HOFFMANN AND S. BOULIANNE Figure 3. Perceived ability to identify misinformation and concerns about misinforma­ tion by country (H3). Note: Unstandardized coefficients with 95% confidence intervals for an OLS regression model. Figure 4. Trust in social media companies and concerns about misinformation by country (H4). Note: Unstandardized coefficients with 95% confidence intervals for an OLS regression model. express slightly higher levels of concern about misinformation on Instagram (H5, b = .09, SE = .02, p < 0.001). This finding replicates in the UK, Canada, and Germany but not in the US and France (Figure 5). We find that as the frequency of one’s network posting political content moderately increases, concerns about misinformation increase (H6, b = .15, SE = .03, p < 0.001). This pattern is consistent in four of five countries with France being the exception (Figure 6). As for network size (H7a), this relationship is not significant in the pooled results (Table 3) and is not significant in four of the five countries. Canada is the exception; network size increases concerns about misinformation on JOURNAL OF ELECTIONS, PUBLIC OPINION AND PARTIES 15 Figure 5. Exposure to political information on Instagram and concerns about misinfor­ mation by country (H5). Note: Unstandardized coefficients with 95% confidence intervals for an OLS regression model. Figure 6. Network posting political content and concerns about misinformation by country (H6). Note: Unstandardized coefficients with 95% confidence intervals for an OLS regression model. Instagram (b = .08, SE = .03, p = .019). Agreement with friends’ political posts (H7b) is not significant in the pooled results nor significant in four of the five countries. France is the exception (b = .14, SE = .05, p = .004). Discussion This study examines Instagram users’ concerns about misinformation on the platform in five Western democratic countries. Understanding the context and drivers of concerns about misinformation is important because these concerns are widespread (Newman et al. 2024), despite limited exposure to 16 C. P. HOFFMANN AND S. BOULIANNE online misinformation found in most studies of Western markets (Allen et al. 2020; Eady et al. 2023; Moore, Dahlke, and Hancock 2023). Concerns about misinformation are associated with a general sense of skepticism or mistrust towards news (Hoes et al. 2022; van der Meer, Hameleers, and Ohme 2023; Van Duyn and Collier 2019;), despite most users overwhelmingly consuming reliable news sources online. Concerns over misinformation may thus weaken institutional trust, and thus harm resilience to disinformation (Humprecht, Esser, and Van Aelst 2020). We study concerns about misinformation on Insta­ gram as this platform has rarely been studied in the past but is widely used among young citizens (Boulianne and Hoffmann 2022; Newman et al. 2023), and is likely to affect young citizens’ perceptions of political information, in particular. We find that, on average, users report moderate concerns about misinfor­ mation on Instagram, with users in Germany and the UK being slightly less concerned and those in France reporting slightly higher concerns. Our research model distinguishes general predictors of concerns over misinfor­ mation and predictors specific to the platform’s information environment. The latter is a distinct contribution to scholarship and provides critical insights to advance our understanding of the context and correlates of con­ cerns about misinformation. Encountering misinformation on social media and the perceived ability to identify misinformation moderately predict concerns over misinformation, but political interest does not. This indicates that when users believe they see mis­ information online, they worry more about the online information environ­ ment – but not necessarily because they fear being misled themselves. Political interest, the perceived ability to identify misinformation and per­ ceived exposure to misinformation on social media all positively correlate with concerns. All three variables are also correlated, with political interest and perceived ability to identify misinformation showing a sizeable correlation (r = .328, p < .001). This finding suggests that politically interested individuals, who engage more with news and political content (Altay 2023; Koc-Michalska et al. 2020) on social media and who are more attuned to elite and media discourse about misinformation (Hoes et al. 2022; Van Duyn and Collier 2019), feel more exposed to misinformation but also feel better able to identify it. Trust in social media companies relates to misinformation concerns – however, we find a small positive relationship. Trust in social media is posi­ tively correlated with Instagram use (r = .084, p < .001), also with network size on Instagram (r = .228, p < .001), and exposure to political content on Instagram (r = .329, p < .001) including seeing friends post political content (r = .366, p < .001). Users trusting social media companies are thus generally more avid users of Instagram, which relates to predictors of misinformation concerns. JOURNAL OF ELECTIONS, PUBLIC OPINION AND PARTIES 17 Turning to the platform-specific predictors, seeing more political content on Instagram, whether in general or specifically from one’s network, moderately increases levels of concerns about misinformation, but network size and political heterogeneity do not. These findings can be related to the conceptual accounts presented above. First, users encoun­ tering more political information may indeed be exposed to more misinfor­ mation (for related findings related to Facebook see Boulianne and Hoffmann 2024b). As noted, seeing political content on Instagram has been characterized as largely incidental, driven by the ties maintained on the platform (cf., Barnidge and Xenos 2024; Thorson and Wells 2016; Thorson et al. 2021). Misinformation on Instagram tends to be posted by lay users (Massey et al. 2020; Lotto et al. 2022). Yet, we did not find a direct relationship between network size and concerns. Network size is strongly correlated with seeing political information (r = .384, p < .001) and specifically, seeing one’s network post political content (r = .415, p < .001). Larger networks, thus, relate to the volume of political content encountered on Instagram. Research into information overload indicates that if users are overwhelmed by the volume of information encountered online, they are more likely to share mis­ information (Apuke et al. 2022; Tandoc and Kim 2023). Also, larger networks tend to be composed of more weak ties, which have been shown to more strongly relate to belief in online misinformation than strong ties (Rossini and Kalogeropoulos 2023). Second, previous research indicates that users who see more political content on social media encounter more politically cross-cutting content that is (mis-)categorized as “misinformation” (cf., Edgerly et al. 2020; Tsang 2022). This is unlikely to explain misinformation concerns on Instagram, however, as the political heterogeneity of users’ networks does not signifi­ cantly relate to misinformation concerns, neither do ideology or political interest. In addition, we find correlational evidence indicating that users maintain politically homogeneous network on Instagram: Frequency of Insta­ gram use (r = .217, p < .001), network size (r = .318, p < .001), and seeing friends post political content (r = .598, p < .001) all correlate positively with agreeing with the political content seen on Instagram. Interestingly, both the frequency of friends posting political content (r = .281, p < .001) and agreement with this political content (r = .221, p < .001) positively correlate with concerns about misinformation. This indicates that seeing even conge­ nial political content on Instagram relates to concerns over misinformation. A third and more likely explanation for our findings revolves around the third-person effect found in previous misinformation research (Altay and Acerbi 2023; Nisbet, Mortenson, and Li 2021). The more users see their ties post political content, the more concerned they are with misinformation on Instagram – despite, as noted above, their network likely being politically 18 C. P. HOFFMANN AND S. BOULIANNE congenial. Thus, users are worried that their Instagram “friends” could become misinformed as they engage more with politics on the platform. Those with higher perceived ability to identify misinformation maintain larger networks on Instagram (r = .144, p < 0.001). Network size correlates with concerns over misinformation (r = .168, p < 0.001). So again, users may not be worried about being misled themselves, but rather about their ties being misinformed. To summarize, our study indicates that Instagram users’ concerns about misinformation on the platform partially relate to the platform’s information environment. More specifically, as political information largely flows through the networks users maintain on the platform (Boulianne and Hoffmann 2024a), misinformation concerns are related to network ties posting political content. This finding can be interpreted in light of the third-person effect (i.e. users worrying about their ties being misinformed, rather than fears of being misinformed oneself). We find no evidence that encounters with politically cross-cutting content play a role. A critical ques­ tion in this context is the ability of users to accurately identify misinforma­ tion. If users overestimate the prevalence of misinformation, concerns can unnecessarily entail problematic downstream effects, such as lower insti­ tutional trust. Our study relies on self-reports about exposure to political content and misinformation. Future research could use web tracking data for more robust measures of exposure to political content and misinformation on Instagram. While self-reports have limitations, they are helpful starting points for further exploratory work. In addition, representative survey data can offer better estimates about public opinion than web tracking data that relies on a small population who are willing to have their use monitored and reported upon. In trying to understand public opinion, perceptions of exposure might be more relevant for understanding people’s views than actual exposure. Yet, future studies may benefit from a more differentiated conceptualization and measurement of concerns about misinformation (e.g. as the relate to oneself, others, social institutions etc.). Finally, we find mostly moderate or small effect sizes in our model, and r-squared of our regression model is also moderate. Future research should therefore take further predictors into consideration. As noted in the introduction, understanding concerns about misinforma­ tion as a distinct phenomenon, apart from objective exposure to misinforma­ tion, is important, as concerns about misinformation inform users’ attitudes and behaviors. If misinformation concerns are driven by third-person effects, users are unlikely to increase their vigilance or engage in behavior to “inoculate” themselves against misinformation (Lewandowsky and Van Der Linden 2021). Still, such concerns can unduly increase mistrust towards the information encountered online and the quality of the information JOURNAL OF ELECTIONS, PUBLIC OPINION AND PARTIES 19 environment provided by social media (cf., Hameleers, Brosius, and de Vreese 2022; Ternovski, Kalla, and Aronow 2022; van der Meer, Hameleers, and Ohme 2023). Also, even if driven by a third-person effect, concerns about misinfor­ mation can lead citizens to support restrictive government interventions to combat misinformation (Jungherr and Rauchfleisch 2024). Understanding the context and correlates of concerns about misinformation is also impor­ tant for devising anti-misinformation interventions. Our findings indicate that bolstering media literacy, in particular: users’ ability to correctly identify misinformation and their ability to realistically gauge misinformation effects on others, may be critical for avoiding negative downstream effects of undue concerns about misinformation (Tay et al. 2023). Disclosure statement No potential conflict of interest was reported by the author(s). Funding This work was supported by Social Sciences and Humanities Research Council of Canada: [grant number 435-2019-04-94]. 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