09/21/2025 | Press release | Distributed by Public on 09/21/2025 08:44
How Political Narratives are distributed on Twitter/X
A study of a team lead by researchers of the Max Planck Institute für Mathematics in the Sciences shows a strikingly clear structural division of the German Twittersphere into two ideological camps - one predominantly left-liberal, the other right-conservative. The work is based on a large-scale analysis of over 19 million tweets covering daily trending topics in Germany between 2021 and 2023. While polarization is not a novel finding in social media research, the authors could identify strong issue alignment across diverse political topics. This means that users consistently position themselves in the same ideological cluster across different issues such as climate change, Covid-19, energy, migration, or media trust. This cross-issue alignment contrasts with previous survey-based research, which typically finds only weak or issue-specific polarization in public opinion.
At the center of this alignment phenomenon are two types of highly active users: influencers, who generate widely shared, ideologically charged content, and multipliers, who primarily act as curators by retweeting content that matches their ideological stance. While influencers resemble traditional opinion leaders such as politicians or media figures, multipliers are less visible yet arguably more influential in shaping the structure of online discourse. The analysis shows that multipliers play a decisive role since their intensive retweet behavior amplifies and bundles ideologically consistent content, thereby facilitating polarized and aligned opinion clusters.
To uncover these patterns, the study combined advanced computational methods. A machine-learning based topic modeling approach inductively classified millions classified millions of tweets into thematic categories across thousands of trending topics, creating a high-dimensional map of public discourse. Retweet activity was then modeled as directed network, with links representing retweets between users. Applying stochastic block modeling - a statistical method for detecting community structure in networks - the researchers identified, for each trend, whether the retweet network is polarized or not, and extracted the clusters that correspond to opposing ideological camps. Finally, an alignment metric was developed to measure how consistently individual users stayed within the same ideological block across topics. Multipliers - whose authenticity is also supported by the study - consistently showed higher alignment scores than influencers, indicating their role in binding issues together.
Polarization is not limited to a few "hot-button" issues but spans multiple political fields simultaneously. The analysis of the top 1,000 influencers and multipliers reveals that multipliers are more active and maintain stronger ideological alignment across topics than influencers. While most political issues are highly aligned, non-political topics such as gaming and music attract different user groups and remain weakly polarized. A similar realignment effect appeared for Ukraine-related discussions, where some right-leaning influencers broke with their cluster's dominant pro-Russian stance - a pattern again less visible among multipliers. Across all topics, multipliers consistently show higher issue alignment than influencers. The topic alignment matrix shows a high issue alignment across topics, except for Music and Gaming, with a gradual difference between strongly aligned issues like Covid, Journalism, and German politics, and less aligned topics like Social politics.
User activity patterns show that multipliers are typically active in a larger number of trends than influencers. A comparison of the size of political clusters highlights further differences. Among the 1000 most retweeted influencers, we observe a majority of accounts belonging to the left-liberal cluster. This is reversed for multipliers: among the 1000 most active multipliers, we observe a majority of users from the right-conservative cluster.
Global and topic-wise cluster membership score for influencers (left) and multipliers (right). A membership score of −1 means that the user belongs to the left-leaning cluster (blue color), +1 to the right-leaning cluster (yellow color). Blank lines in the matrix mean that the user did not participate in any retweet network associated to the given topic. We observe that multipliers are more active and aligned across topics than influencers.
The authors highlight the importance of considering the role of social media in shaping public opinion and the need for further research into the mechanisms driving polarization. The study has limitations that call for further research, such as the need to shed light on the discursive reasons of issue alignment, which the authors plan on investigating through the lens of conflicting narratives. Further research is needed to explore the alignment of regular users and to determine if similar patterns of polarization exist on other social media platforms. Preliminary findings suggest that consistent polarization and issue alignment may hold for the majority of users, and that influential hyper-active users on other platforms, such as Facebook, may have similar effects as multipliers on Twitter.
The study was funded by the European Union's Horizon Europe project Social Media for Democracy (SoMe4) studying the impact of social media on the public sphere and liberal democracy, by the French government under management of Agence Nationale de Recherche as part of the "Investissements d'avenir" program, and by the "Digital News Dynamics" research group at Weizenbaum Institute Berlin.