Information gerrymandering and undemocratic decisions
Abstract
People must integrate disparate sources of information when making decisions, especially in social contexts. But information does not always flow freely. It can be constrained by social networks 1-3 and distorted by zealots and automated bots 4. Here we develop a voter game as a model system to study information flow in collective decisions. Players are assigned to competing groups (parties) and placed on an 'influence network' that determines whose voting intentions each player can observe. Players are incentivized to vote according to partisan interest, but also to coordinate their vote with the entire group. Our mathematical analysis uncovers a phenomenon that we call information gerrymandering: the structure of the influence network can sway the vote outcome towards one party, even when both parties have equal sizes and each player has the same influence. A small number of zealots, when strategically placed on the influence network, can also induce information gerrymandering and thereby bias vote outcomes. We confirm the predicted effects of information gerrymandering in social network experiments with n = 2,520 human subjects. Furthermore, we identify extensive information gerrymandering in real-world influence networks, including online political discussions leading up to the US federal elections, and in historical patterns of bill co-sponsorship in the US Congress and European legislatures. Our analysis provides an account of the vulnerabilities of collective decision-making to systematic distortion by restricted information flow. Our analysis also highlights a group-level social dilemma: information gerrymandering can enable one party to sway decisions in its favour, but when multiple parties engage in gerrymandering the group loses its ability to reach consensus and remains trapped in deadlock.
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Recent work suggests that network structural effects can lead to "information gerrymandering" that induces undemocratic outcomes whereby a majority of the electorate votes against the electorate's interest.
“Recent work suggests that network structural effects can lead to “information gerrymandering” that induces undemocratic outcomes whereby a majority of the electorate votes against the electorate’s interest”
From Stewardship of global collective behavior (2021) · cites this paper as [97]
Even a small number of agents with aggressive attitudes can have a substantial influence on the majority view (information gerrymandering).
“even a small number of agents with aggressive attitudes can have a substantial influence on the majority view, a process called “information gerrymandering” (66).”
From Troll and divide: the language of online polarization (2022) · cites this paper as [66]
Exposure to polarizing attitudes even produced by a small number of agents can have a devastating effect on political compromise in a social network.
“Exposure to polarizing attitudes even produced by a small number of agents can have a devastating effect on political compromise in a social network”
From Troll and divide: the language of online polarization (2022) · cites this paper as [66]
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- Authors
- Stewart, A. J., Mosleh, M., Diakonova, M., Arechar, A. A., Rand, D. G., & Plotkin, J. B.
- Affiliations
- University of Houston (US)
- Massachusetts Institute of Technology (US)
- University of Oxford (GB)
- Centro de Investigación y Docencia Económicas (MX)
- University of Pennsylvania (US)
- Corresponding author
- Stewart, Alexander J.
- ORCID
- Venue
- Nature
- Published
- 2019-09-04
- Volume
- 573
- Issue
- 7772
- Pages
- 117-121
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2972275627
- Cited by
- 176
- References
- 29
- Citations by year
- 2026: 5 · 2025: 14 · 2024: 18 · 2023: 31 · 2022: 32 · 2021: 48 · 2020: 22 · 2019: 6
- FWCI
- 12.49
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Opinion Dynamics and Social Influence
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Game Theory and Voting Systems
- Keywords
- group decision making, influence networks, Zealots, bots, social dilemmas, democratic legitimacy, information flow, political polarization, online political discussion, United States Congress
- MeSH terms
- Decision Making, Democracy, Game Theory, Group Processes, Humans, Models, Theoretical, Politics, Truth Disclosure, Bias, Knowledge, Social Networking, Social Media
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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