mlsanityData to 14 Oct 2026

CommunityLM: Probing Partisan Worldviews from Language Models

arXiv 2209.07065 ↗First posted 15 Sep 2022cs.SI cs.AI cs.CLcited by 36

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Abstract (arXiv)

As political attitudes have diverged ideologically in the United States, political speech has diverged lingusitically. The ever-widening polarization between the US political parties is accelerated by an erosion of mutual understanding between them. We aim to make these communities more comprehensible to each other with a framework that probes community-specific responses to the same survey questions using community language models CommunityLM. In our framework we identify committed partisan members for each community on Twitter and fine-tune LMs on the tweets authored by them. We then assess the worldviews of the two groups using prompt-based probing of their corresponding LMs, with prompts that elicit opinions about public figures and groups surveyed by the American National Election Studies (ANES) 2020 Exploratory Testing Survey. We compare the responses generated by the LMs to the ANES survey results, and find a level of alignment that greatly exceeds several baseline methods. Our work aims to show that we can use community LMs to query the worldview of any group of people given a sufficiently large sample of their social media discussions or media diet.

Key facts. Cited by 36 papers in the map (data through 14 Oct 2026). Builds on 17 of its 31 references that are in the map. First posted on arXiv 15 Sep 2022.

Builds on

17 of 31 references.

References · 17

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  2. 2020Language Models are Few-Shot Learnerscited by 32,419
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5 more
  1. 2022TimeLMs: Diachronic Language Models from Twittercited by 131
  2. 2019Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootingscited by 67
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 10; 2024: 10; 2025: 11; 2026: 4.

36 papers.

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  1. 2023Whose Opinions Do Language Models Reflect?cited by 773
  2. 2023Towards Measuring the Representation of Subjective Global Opinions in Language Modelscited by 437
  3. 2023From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Modelscited by 260
  4. 2023Generative Language Models Exhibit Social Identity Biasescited by 111
  5. 2023Training Socially Aligned Language Models on Simulated Social Interactionscited by 78
  6. 2022Moral Mimicry: Large Language Models Produce Moral Rationalizations Tailored to Political Identitycited by 74
  7. 2023Questioning the Survey Responses of Large Language Modelscited by 74
  8. 2023On the steerability of large language models toward data-driven personascited by 53
  9. 2024Virtual Personas for Language Models via an Anthology of Backstoriescited by 51
  10. 2024Random Silicon Sampling: Simulating Human Sub-Population Opinion Using a Large Language Model Based on Group-Level Demographic Informationcited by 49
  11. 2024Stereotype or Personalization? User Identity Biases Chatbot Recommendationscited by 34
  12. 2025Linear Representations of Political Perspective Emerge in Large Language Modelscited by 32
24 more
  1. 2024AI for social science and social science of AI: A Surveycited by 29
  2. 2024How Susceptible are Large Language Models to Ideological Manipulation?cited by 26
  3. 2025Language Agents as Digital Representatives in Collective Decision-Makingcited by 16
  4. 2023Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challengescited by 13
  5. 2024Beyond Partisan Leaning: A Comparative Analysis of Political Bias in Large Language Modelscited by 13
  6. 2024Persona Setting Pitfall: Persistent Outgroup Biases in Large Language Models Arising from Social Identity Adoptioncited by 9
  7. 2024Skin-in-the-Game: Decision Making via Multi-Stakeholder Alignment in LLMscited by 8
  8. 2025What Is The Political Content in LLMs' Pre- and Post-Training Data?cited by 7
  9. 2025textttBluePrint: A Social Media User Dataset for LLM Persona Evaluation and Trainingcited by 6
  10. 2023Exposing Bias in Online Communities through Large-Scale Language Modelscited by 5
  11. 2025Political Ideology Shifts in Large Language Modelscited by 5
  12. 2026Identity, Cooperation and Framing Effects within Groups of Real and Simulated Humanscited by 5
  13. 2024Leveraging Machine Learning to Identify Gendered Stereotypes and Body Image Concerns on Diet and Fitness Online Forumscited by 3
  14. 2024Bridging Dictionary: AI-Generated Dictionary of Partisan Language Usecited by 3
  15. 2025Examining Alignment of Large Language Models through Representative Heuristics: The Case of Political Stereotypescited by 3
  16. 2023Is the U.S. Legal System Ready for AI's Challenges to Human Values?cited by 2
  17. 2025HugAgent: A Human Simulation Benchmark for Individual-Level Reasoningcited by 2
  18. 2025Hedging and Non-Affirmation: Quantifying LLM Alignment on Questions of Human Rightscited by 1
  19. 2025Ideology-Based LLMs for Content Moderationcited by 1
  20. 2025Community-Aligned Behavior Under Uncertainty: Evidence of Epistemic Stance Transfer in LLMscited by 0
  21. 2025What Helps Language Models Predict Human Beliefs: Demographics or Prior Stances?cited by 0
  22. 2026Rethinking Indic AI from a Lens of Cultural Heritage Preservationcited by 0
  23. 2026Video2Reaction: Mapping Video to Audience Reaction Distribution in the Wildcited by 0
  24. 2026Geospatial AI, Dataverse Metadata, and the Study of Place-Based Governmentcited by 0