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Identity effects in social media

Nature Human Behaviour volume 7, pages 27–37 (2023)Cite this article

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Abstract

Identity cues appear ubiquitously alongside content in social media today. Some also suggest universal identification, with names and other cues, as a useful deterrent to harmful behaviours online. Unfortunately, we know little about the effects of identity cues on opinions and online behaviours. Here we used a large-scale longitudinal field experiment to estimate the extent to which identity cues affect how people form opinions about and interact with content online. We randomly assigned content produced on a social news aggregation website to ‘identified’ and ‘anonymous’ conditions to estimate the causal effect of identity cues on how viewers vote and reply to content. The effects of identity cues were significant and heterogeneous, accounting for between 28% and 61% of the variation in voting associated with commenters’ production, reputation and reciprocity. Our results also showed that identity cues cause people to vote on content faster (consistent with heuristic processing) and to vote according to content producers’ reputations, production history and reciprocal votes with content viewers. These results provide evidence that rich-get-richer dynamics and inequality in social content evaluation are mediated by identity cues. They also provide insights into the evolution of status in online communities. From a practical perspective, we show via simulation that social platforms may improve content quality by including votes on anonymized content as a ranking signal.

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Fig. 1: Associations between values of moderator covariates and the effect of identity on interactions.
Fig. 2: Distribution of voting duration and estimated identity effect.
Fig. 3: Algorithmic ranking simulations.
Fig. 4: Average treatment effect of identity for each month of the experiment.
Fig. 5: Causal diagram indicating the interference we test for and the type we rule out by assumption.
Fig. 6: Estimates of spillover effects of the anonymous treatment.

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Data availability

An anonymized version of the data supporting this study is retained indefinitely for reproducibility. The data can be accessed from the authors by signing a non-disclosure agreement available at the following GitHub repository: https://github.com/seanjtaylor/identify_effects_in_social_media. The NDA requires that researchers provide their affiliation and attest that they will only use the data for reproduction and that no attempt will be made to re-engineer the identities of users or the platform.

Code availability

The code supporting this study is available at the following GitHub repository: https://github.com/seanjtaylor/identify_effects_in_social_media.

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Acknowledgements

We thank members of the MIT Initiative on the Digital Economy for valuable feedback. L.M. acknowledges support from the Israel Science Foundation (Grant 2566/21) and the David Goldman Data-Driven Innovation Research Centre for supporting this research. The authors received no specific funding for this work.

Author information

Authors and Affiliations

  1. Independent Researcher, Oakland, CA, USA

    Sean J. Taylor

  2. The Hebrew University Business School, Hebrew University of Jerusalem, Jerusalem, Israel

    Lev Muchnik

  3. Microsoft Research, Herzliya, Israel

    Lev Muchnik

  4. MIT Sloan School of Management, Cambridge, MA, USA

    Madhav Kumar & Sinan Aral

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  2. Lev Muchnik
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  4. Sinan Aral
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Contributions

S.J.T., L.M. and S.A. performed the research design and data analysis. S.J.T., M.K. and S.A. did the writing.

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Correspondence to Sinan Aral.

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Nature Human Behaviour thanks Johan Ugander, Marijn Keijzer and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Sections A.1–A.7, Figs. B3–B7 and Tables C3–C5.

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Taylor, S.J., Muchnik, L., Kumar, M. et al. Identity effects in social media. Nat Hum Behav 7, 27–37 (2023). https://doi.org/10.1038/s41562-022-01459-8

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