Magdalena Wojcieszak

The news media ecosystem is undergoing substantial changes; news avoidance is growing, news influencers are becoming prominent, and mainstream news outlets increasingly draw from influencers to design “social-first” content for social media platforms. Yet, the effects of these new news producers are not well understood, particularly compared to those of traditional news. We develop a framework distinguishing traditional news, news influencers, and social-first news through three pathways (informational, relational, experiential), positing that distinctive content features influence audience perceptions (credibility, social presence and engagement), which — in turn — influence democratic attitudes. We test this framework in a preregistered, two-week longitudinal online field experiment (N = 1,284), randomly assigning U.S. Instagram and TikTok users to follow traditional news, news influencers, social first news, or non-news control accounts. Following all news types increases trust in social media news, while traditional news additionally increases trust in news more broadly, and those assigned to follow traditional news report the highest intent to continue following these accounts post-study. Mediation analyses support the informational and relational pathways, but not the experiential: credibility predicts greater knowledge, discernment, and trust, while social presence predicts greater political interest and trust. These patterns do not depend on compliance, prior news consumption, or socio-demographics. By classifying all videos posted by our treatment news accounts during the study period, we also show that theoretically salient content features differ consistently across types of news. We discuss the implications of our findings for the theorizing of the online information ecosystem, and for journalistic practitioners.

We examine the conditions in which people reject cross-cutting news in naturalistic settings of online comments. Theoretically, we account for article content and source to test whether commenters’ rejection and its intensity depend on whether cross-cutting news (a) is hostile to their in-group or favorable to the out-group and (b) is “unexpected” (from in-group sources) or “expected” (from out-group sources). Methodologically, we use online traces from news aggregators in South Korea (SK; 7,607 comments) and the United States (116,308 comments). We find that most commenters (79% in SK and 64% in the United States) reject cross-cutting news, with left-leaning commenters expressing stronger rejection than right-leaning commenters. Regarding article content, the SK commenters more strongly rejected in-group hostility, while the U.S. commenters rejected out-group favoritism more. Regarding article source, SK commenters more strongly rejected unexpected cross-cutting news from in-group sources than expected cross-cutting news from out-group sources. We discuss the implications of these findings.

Political polarization poses major societal risks, yet a globally relevant, interdisciplinary understanding remains lacking, as nearly half of all studies focus on the United States. We argue for renewed effort to bring global equity to polarization research, highlighting insights robust across countries, those unique to specific contexts, and key literature gaps. Closing these gaps means overcoming cultural and systemic barriers, including data-access restrictions and misaligned incentives. It also demands interdisciplinarity bridging traditional approaches and those addressing the polarizing role of the internet, social media, and AI. Otherwise, efforts to counter polarization, and its democratic harms, risk resting on unsuitable evidence.

Despite concern about exposure to content from untrustworthy sources on social media, little is known about the frequency or effects of exposure to their content. We examine 2020 data from all active US adults on Facebook and Instagram to measure exposure to content from Pages, groups, and web domains on Facebook and public accounts on Instagram that repeatedly publish misinformation. We find that average users saw relatively little content in their feeds from these untrustworthy sources; exposure was highly concentrated. A multimonth field experiment during the 2020 election among consenting users reduced feed-based exposure to content from untrustworthy sources by approximately 70% on both platforms but had no measurable effects on numerous preregistered outcomes, even among participants with high pretreatment exposure. Our results demonstrate that a feasible platform intervention can successfully reduce exposure to content from untrustworthy sources but suggest that these changes are unlikely to have immediate effects on attitudes and beliefs.

Democratic challenges are often attributed to the spread of misleading, untrustworthy, or biased information, leading scholars to focus on minimizing exposure to such “bad” content online. Instead, we introduce a scalable intervention to put factual and verified public affairs information in users’ social media feeds to make them better informed and more resilient to various online threats. We conducted 48 field quasi-experiments using Instagram ads targeting news non-users to enhance their belief accuracy, democratic attitudes, and behavioral intentions related to climate change, COVID-19 vaccines, media literacy, and election integrity. The treatment videos reached 2,496,878 Instagram accounts, 690,470 users watched at least 50% of the video, and 40,584 of those users completed post-test assessment. The intervention was effective: 46 out of 48 of the quasi-experiments had positive effect sizes and 40 out of 48 achieved statistical significance. The intervention predicted not only belief accuracy but also attitudes, media literacy, and — to some extent — behavioral intentions related to vaccination. These patterns emerged across topics, did not dissipate with time (two of three climate change quasi-experiments show continued effects), and were not contingent on persuasive appeals and format features presented in the ads.

News and politics constitute a small fraction of people’s information diets, and many individuals avoid news and public affairs information, a phenomenon that has a range of detrimental democratic consequences. Extensive research investigates the extent and the effects of news avoidance and news non-use. This article contributes to this scholarship in two ways. First, we conduct a systematic review of 125 studies, which empirically test the predictors of news avoidance and non-use to identify individual, social, and algorithmic/design factors associated with this phenomenon. We find that extant research focuses on individual over broader structural factors. Second, we propose a multi-actor framework for solutions to news avoidance and non-use. We outline strategies by news organizations, governments, and platforms, showing how each actor is suited to address distinct aspects of the phenomenon. As these are likely insufficient or uninterested in intervening, we also propose three additional sets of solutions: nudges, non-political content, and media literacy. We also show that the subfields proposing and testing the various strategies are largely disconnected from the scholarship on news avoidance and non-use. In doing so, we present a research agenda to clarify the correlates of news non-use and to understand what strategies might best address this problem.

Deceptive online networks are coordinated efforts that use identity deception to pursue strategic political or financial goals. During the US 2020 elections, these networks reached at least 37 million Facebook and 3 million Instagram users, representing 15% and 2% of the platforms' active US adult users, respectively. Only 3 networks out of 49-1 network with explicitly political aims and 2 that appeared to use politics as a lure for profit-were responsible for over 70% of users reached. Notably, accounts unaffiliated with the networks played an important role in facilitating this reach by resharing content the three networks produced. Deceptive networks, regardless of whether their goals were political or financial, reached users who were older, more conservative, more frequently exposed to content from untrustworthy sources, and spent more time on Facebook.

We study the effects of social media political advertising by randomizing subsets of 36,906 Facebook users and 25,925 Instagram users to have political ads removed from their news feeds for 6 weeks before the 2020 US presidential election. We show that most presidential ads were targeted towards parties’ own supporters and that fundraising ads were the most common. On both Facebook and Instagram, we found no detectable effects of removing political ads on political knowledge, polarization, perceived legitimacy of the election, political participation (including campaign contributions), candidate favourability and turnout. This was true overall and for both Democrats and Republicans separately.

Can the news help people be more resilient to misinformation? Altay et al. found that news use increases surveillance knowledge and awareness of true and false news, while decreasing belief in false news. We conducted a two-wave panel survey ( N = 3,395) to replicate these findings in two new countries: France and Germany. The replication reinforces the conclusions of the original study: we found that higher news consumption predicted greater surveillance knowledge acquisition across the waves, as well as greater awareness of and belief in true news stories. News consumption also increased awareness of false news stories without increasing belief in false news stories. These findings strengthen the idea that news helps people become more informed and better at discerning truth from falsehoods.

Platforms, especially Facebook, are primary news sources in the US. In its widely criticized "War on News," Meta algorithmically deprioritized news and political content. We use data from 40 news organizations (5,243,302 Facebook posts, 7,875,372,958 user reactions) and 21 non-news pages (396,468 posts; 1,909,088,308 reactions) between January 1, 2016 and February 13, 2025 to examine how these changes influenced news visibility on the platform. Reactions to news declined by 78% between 2021 and 2024 while reactions to non-news pages increased, indicating targeted suppression of news visibility. Low-quality sources were especially suppressed, yet the 2025 end to "War on News" increased user reactions to news, especially low-quality ones. These changes do not reflect decreased news supply, Facebook user base, or interest in news over this period.