Research

CSMaP is a leading academic research institute studying the ever-shifting online environment at scale. We publish peer-reviewed research in top academic journals, produce rigorous reports and analyses on policy relevant topics, and develop open source tools and methods to support the broader scholarly community.

Academic Research

  • Journal Article

    Information Diets are More Diverse in Attention than in Engagement

    Sociological Science, 2026

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    What political content do we pay attention to online? Diverse political information is essential for democratic competence, yet online media raises concerns about fragmented information diets. Research on selective exposure highlights how social media can foster ideological echo chambers, while other studies emphasize incidental exposure to diverse viewpoints. A critical limitation is measurement: existing research primarily uses engagement metrics (e.g., likes or shares), neglecting passive exposure or attention—what users notice but do not interact with. In this study, we address this gap through an experimental platform that separately records attention and engagement. Our findings indicate that the ideology-engagement association is about seven times the magnitude of the ideology-attention association. This underscores the importance of measuring attention, rather than solely engagement, to accurately assess the diversity of online information diets.

    Date Posted

    Jul 21, 2026

  • Working Paper

    Evaluating Echo Chambers, Rabbit Holes, and Radicalization Pathways on YouTube

    Political Communication, 2026

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    To what extent does the YouTube recommendation algorithm push users into echo chambers, rabbit holes, or radicalization pathways? Using a novel method to estimate the ideology of YouTube videos and an original audit design, we find that YouTube users experience mild ideological echo chambers, but these appear to be driven primarily by user behavior.  We also demonstrate that the recommendation algorithm prioritizes content that is similar to what the user is currently watching, producing “content rabbit holes”. However, we do not find evidence of radicalization pathways where users are driven into increasingly extreme content rabbit holes. Instead, we find that YouTube’s recommendations move users, regardless of ideology, toward moderately conservative content and an increasingly narrow range of ideological content the longer they follow YouTube’s recommendations.

    Date Posted

    Jun 10, 2026

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Reports & Analysis

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Data Collections & Tools

As part of our project to construct comprehensive data sets and to empirically test hypotheses related to social media and politics, we have developed a suite of open-source tools and modeling processes.