{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/communitylm-probing-partisan-worldviews-from","title":"CommunityLM: Probing Partisan Worldviews from Language Models","arxiv_id":"2209.07065","date":"2022-09-15","proceeding":"COLING 2022 10","authors":["Hang Jiang","Doug Beeferman","Brandon Roy","Deb Roy"],"abstract":"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.","url_abs":"https://arxiv.org/abs/2209.07065v1","url_pdf":"https://arxiv.org/pdf/2209.07065v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"communitylm-probing-partisan-worldviews-from","repo_url":"https://github.com/hjian42/communitylm","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"CC0-1.0"}}],"tasks":[{"task_slug":"survey","task_name":"Survey"}],"methods":[{"method_slug":null,"method_name":"American"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2209.07065","atlas_url":"https://app.syntology.ai/?focus=2209.07065","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2209.07065"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/hjian42/communitylm","reach":{"status":"ok","spdx":"CC0-1.0"}}],"summary":{"ran":3},"by_repo_kind":{"official":{"samples":3,"ran":3,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"2d320d348bd9418a","entry":"compute_group_lexicon_sentiment","repo":"hjian42/communitylm","repo_kind":"official","path":"inference/compute_group_stance.py","file_url":"https://github.com/hjian42/communitylm/blob/HEAD/inference/compute_group_stance.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"CC0-1.0","inline_ok":true,"mcp_get_code":{"code_sha256":"2d320d348bd9418a"}},{"code_sha256_prefix":"3c60c432e6ad5397","entry":"compute_group_sentiment","repo":"hjian42/communitylm","repo_kind":"official","path":"inference/compute_group_stance.py","file_url":"https://github.com/hjian42/communitylm/blob/HEAD/inference/compute_group_stance.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"CC0-1.0","inline_ok":true,"mcp_get_code":{"code_sha256":"3c60c432e6ad5397"}},{"code_sha256_prefix":"274e3acb928c429d","entry":"generate_with_a_prompt","repo":"hjian42/communitylm","repo_kind":"official","path":"inference/generate_community_opinion.py","file_url":"https://github.com/hjian42/communitylm/blob/HEAD/inference/generate_community_opinion.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"CC0-1.0","inline_ok":true,"mcp_get_code":{"code_sha256":"274e3acb928c429d"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}