ValueScope: Unveiling Implicit Norms and Values via Return Potential Model of Social Interactions
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Abstract (arXiv)
This study introduces ValueScope, a framework leveraging language models to quantify social norms and values within online communities, grounded in social science perspectives on normative structures. We employ ValueScope to dissect and analyze linguistic and stylistic expressions across 13 Reddit communities categorized under gender, politics, science, and finance. Our analysis provides a quantitative foundation showing that even closely related communities exhibit remarkably diverse norms. This diversity supports existing theories and adds a new dimension--community preference--to understanding community interactions. ValueScope not only delineates differing social norms among communities but also effectively traces their evolution and the influence of significant external events like the U.S. presidential elections and the emergence of new sub-communities. The framework thus highlights the pivotal role of social norms in shaping online interactions, presenting a substantial advance in both the theory and application of social norm studies in digital spaces.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 25 of its 80 references that are in the map. First posted on arXiv 2 Jul 2024.
Builds on
25 of 80 references.
References · 25
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13 more
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Built on by
Citing papers per year: 2024: 3; 2025: 8; 2026: 1.
12 papers.
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- 2025PrefPalette: Personalized Preference Modeling with Latent Attributescited by 15
- 2025Out of Style: RAG's Fragility to Linguistic Variationcited by 10
- 2024SPICA: Retrieving Scenarios for Pluralistic In-Context Alignmentcited by 6
- 2025Social Story Frames: Contextual Reasoning about Narrative Intent and Receptioncited by 3
- 2025PICACO: Pluralistic In-Context Value Alignment of LLMs via Total Correlation Optimizationcited by 2
- 2024Algorithmic Behaviors Across Regions: A Geolocation Audit of YouTube Search for COVID-19 Misinformation Between the United States and South Africacited by 1
- 2025Is Active Persona Inference Necessary for Aligning Small Models to Personal Preferences?cited by 1
- 2025Decoding the Rule Book: Extracting Hidden Moderation Criteria from Reddit Communitiescited by 1
- 2025Who's Asking? Simulating Role-Based Questions for Conversational AI Evaluationcited by 1
- 2026Growth First, Care Second? Tracing the Landscape of LLM Value Preferences in Everyday Dilemmascited by 1
- 2026Growth First, Care Second? Tracing the Landscape of LLM Value Preferences in Everyday Dilemmas4 Feb 2026
- 2025Social Story Frames: Contextual Reasoning about Narrative Intent and Reception17 Dec 2025
- 2025Who's Asking? Simulating Role-Based Questions for Conversational AI Evaluation19 Oct 2025
- 2025Decoding the Rule Book: Extracting Hidden Moderation Criteria from Reddit Communities3 Sep 2025
- 2025PICACO: Pluralistic In-Context Value Alignment of LLMs via Total Correlation Optimization22 Jul 2025
- 2025PrefPalette: Personalized Preference Modeling with Latent Attributes17 Jul 2025
- 2025Is Active Persona Inference Necessary for Aligning Small Models to Personal Preferences?19 May 2025
- 2025Out of Style: RAG's Fragility to Linguistic Variation11 Apr 2025
- 2025ALFA: Aligning LLMs to Ask Good Questions A Case Study in Clinical Reasoning20 Feb 2025
- 2024SPICA: Retrieving Scenarios for Pluralistic In-Context Alignment16 Nov 2024
- 2024Controllable Safety Alignment: Inference-Time Adaptation to Diverse Safety Requirements11 Oct 2024
- 2024Algorithmic Behaviors Across Regions: A Geolocation Audit of YouTube Search for COVID-19 Misinformation Between the United States and South Africa16 Sep 2024