With T. Chuai, M. Pilarski, D. Restrepo-Amariles, A. Troussel-Clément, G. Lenzini, N. Pröllochs
Community-based fact-checking is a promising approach to verify social media content and correct misleading posts at scale. Yet, causal evidence regarding its effectiveness in reducing the spread of misinformation on social media is missing. Here, we performed a large-scale empirical study to analyze whether community notes reduce the spread of misleading posts on X. Using a Difference-in-Differences design and repost time series data for N=237,677 (community fact-checked) cascades that had been reposted more than 431 million times, we found that exposing users to community notes reduced the spread of misleading posts by, on average, 62.0%. Furthermore, community notes increased the odds that users delete their misleading posts by 103.4%. However, our findings also suggest that community notes might be too slow to intervene in the early (and most viral) stage of the diffusion. Our work offers important implications to enhance the effectiveness of community-based fact-checking approaches on social media.
How does the success of the far right affect the immigration rhetoric of mainstream parties and their electoral performance? To explore this question, we exploit the gradual success of the Front National in French parliamentary elections since its creation in 1972. We find that the electoral success of far-right parties came at the expense of a decline in the vote share of mainstream right-wing parties. Using a comprehensive textual analysis of the universe of candidate manifestos from 1968 to 1997, we show that mainstream right-wing candidates respond to the success of far-right parties by increasing the salience of immigration in their manifestos. This strategic adjustment mitigates electoral losses to far-right competitors. In contrast, the strategic response of mainstream left-wing candidates is to reduce the prominence of immigration in their manifestos to reduce their electoral losses.
Social media usage is often cited as a potential driver behind the rising suicide rates, especially for teens and young adults. However, distinguishing the causal effect—whether social media increases the risk of suicide—from reverse causality, where individuals already at higher risk of suicide are more likely to use social media, remains a significant challenge. In this paper, we employ an instrumental variable approach to examine the quasi-exogenous geographical adoption of Twitter and investigate the causal relationship between social media use and suicide rates. Our analysis first demonstrates that Twitter’s geographical adoption was driven by the presence of certain users at the 2007 SXSW festival, which led to long-term disparities in adoption rates across countries. Then, using a two-stage least squares (2SLS) regression and controlling for a wide range of socio-economic and demographic factors, we find no significant relationship between Twitter adoption and suicide rates at the county level in the United States.
We investigate political asymmetry in misinformation sharing on social media, specifically examining the frequency of misinformation shared by Republicans compared to Democrats. Utilizing crowd-sourced assessments from X’s Community Notes program, we examine whether Republicans share more misinformation even when the definition of misinformation is community-driven rather than determined by centralized fact-checkers or platform moderators. Our dataset includes all English-language Community Notes on X, categorized based on whether the content achieved “helpful” status, indicating a consensus of potentially misleading information. We employ a probit model to control for tweet and user-level characteristics, such as sentiment, account age, and follower count. Our analysis reveals that Republicans post misinformation at a significantly higher rate than Democrats, even after accounting for potential confounding factors. Additionally, we verify the political balance of the Community Notes program, finding no significant over-representation of Democratic raters, and we confirm that the increase in misinformation is not solely a byproduct of overrepresentation of Republicans on X. These findings support the hypothesis of political asymmetry in misinformation sharing, highlighting the potential of crowd-sourced fact-checking as a credible, inclusive tool for misinformation moderation.
We propose a new measure of conflict at a daily frequency using data from the Global Database of Events, Language, and Tone (GDELT). Our methodology allows us to disentangle conflict discussed by the media of a country from conflict involving the country in question and covered by global sources. We first demonstrate that the global index correlates with the Geopolitical Risk Index (GPR) from Caldara et al. (2020). Conflicts involving threats, force posture, and reductions in relations have the largest correlations with the GPR. We then analyze the relationship between conflict and stock returns across 44 countries over the period 2015-2023. We find that an increase in conflict is correlated with lower contemporaneous returns and that the primary drivers of market movements are assaults and reductions in relations. Both local coverage of global conflicts and global coverage of local conflicts affect stock returns, underscoring the importance of constructing more diverse indicators of geopolitical risk from a larger and more varied set of news sources.
We propose a novel measure of investor attention by analyzing messages sent on Twitter around European Central Bank announcements. We then examine the market impact of the ECB decisions and press conferences, contingent on the level of investor attention prior to the announcements, across a wide array of assets (stocks, bonds, OIS, and exchange rates). We find that absolute price changes are higher when investor attention is elevated before the announcements. This effect is stronger in the press release window than in the press conference window, especially when focusing on messages from users who self-describe themselves as investors. Investor attention also magnifies the impact of monetary policy surprises. Our results suggest that central bankers can use the level of attention prior to the announcements to enhance their anticipation of the market's reaction to the announcement.