ValueScope: Unveiling Implicit Norms and Values via Return Potential Model of Social Interactions (2024.findings-emnlp)
Copied to clipboard
Chan Young Park, Shuyue Stella Li, Hayoung Jung, Svitlana Volkova, Tanu Mitra, David Jurgens, Yulia Tsvetkov
| Challenge: | VALUESCOPE is a framework that quantifies social norms and values within online communities. |
| Approach: | They propose a framework that uses language models to quantify social norms and values within online communities. |
| Outcome: | The proposed framework delineates differences in social norms and tracks evolution of norms in online communities and influence of significant external events like the U.S. presidential elections and the emergence of new sub-communities. |
Similar Papers
Detecting Community Sensitive Norm Violations in Online Conversations (2021.findings-emnlp)
Copied to clipboard
Chan Young Park, Julia Mendelsohn, Karthik Radhakrishnan, Kinjal Jain, Tushar Kanakagiri, David Jurgens, Yulia Tsvetkov
| Challenge: | Existing efforts to identify unacceptable behavior have focused on toxicity as the sole form of community norm violation. |
| Approach: | They propose a dataset that focuses on a more complete spectrum of community norms and their violations in local conversational and global contexts. |
| Outcome: | The proposed model improves the detection of community norm violations in local conversational and global contexts. |
Investigating Human Values in Online Communities (2025.naacl-long)
Copied to clipboard
| Challenge: | Existing value frameworks struggle with sample sizes and rely on selfreported surveys to calculate values. |
| Approach: | They propose a method to computationally analyse values on Reddit using in-domain and out-of-domain human annotations to train a value relevance and a polarity classifier. |
| Outcome: | The proposed method can be used to analyse values on reddit using human annotations and human annotation. |
Moral Stories: Situated Reasoning about Norms, Intents, Actions, and their Consequences (2021.emnlp-main)
Copied to clipboard
| Challenge: | aaron carroll: in social settings, human behavior is governed by unspoken rules of conduct rooted in societal norms . carroll and colleagues examine whether language generation models can serve as behavioral priors if they are not . they say we examine whether they can generate descriptions of actions that accomplish predefined goals . |
| Approach: | They propose to combine multiple expert models to improve quality of generated actions, consequences, and norms. |
| Outcome: | The proposed models significantly improve the quality of generated actions, consequences, and norms compared to baselines. |
How Inclusively do LMs Perceive Social and Moral Norms? (2025.findings-naacl)
Copied to clipboard
| Challenge: | Language models (LMs) are used in decision-making systems and as interactive assistants. |
| Approach: | They propose to prompt 11 LMs on rules-of-thumb and compare their outputs with 100 human annotators. |
| Outcome: | The proposed model is compared with 100 human annotators to find out if they are inclusive of diverse human values. |
Measuring Social Norms of Large Language Models (2024.findings-naacl)
Copied to clipboard
| Challenge: | Existing datasets that evaluate a general understanding of social science are inadequate to understand social norms. |
| Approach: | They propose a multi-agent framework to improve large language models’ ability to understand social norms by comparing them to elementary students. |
| Outcome: | The proposed framework improves large language models to be on par with humans. |
NORMSAGE: Multi-Lingual Multi-Cultural Norm Discovery from Conversations On-the-Fly (2023.emnlp-main)
Copied to clipboard
| Challenge: | Existing methods to understand acceptable behavior have focused on a single culture and manually built datasets from non-conversational settings. |
| Approach: | They propose a framework to automatically extract culture-specific norms from multi-lingual conversations. |
| Outcome: | The proposed framework extracts culture-specific norms from multi-lingual conversations. |
Unifying Data Perspectivism and Personalization: An Application to Social Norms (2022.emnlp-main)
Copied to clipboard
| Challenge: | Obtaining a single ground truth is not possible or necessary for subjective tasks. |
| Approach: | They propose a set of personalization methods to model annotators and compare their effectiveness for predicting social norms. |
| Outcome: | The proposed model outperforms existing models and compares performance across subsets of social situations that vary by the closeness of the relationship between parties in conflict. |
ValueBench: Towards Comprehensively Evaluating Value Orientations and Understanding of Large Language Models (2024.acl-long)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) are transforming diverse fields and gaining increasing influence as human proxies. |
| Approach: | They propose a psychometric evaluation pipeline grounded in realistic human-AI interactions to probe value orientations and novel tasks for evaluating value understanding in an open-ended value space. |
| Outcome: | The proposed evaluation pipeline is grounded in realistic human-AI interactions and performs tasks that approximate expert conclusions in value-related extraction and generation tasks. |
Value-Spectrum: Quantifying Preferences of Vision-Language Models via Value Decomposition in Social Media Contexts (2025.acl-long)
Copied to clipboard
| Challenge: | Recent advances in Vision-Language Models (VLMs) have broadened the scope of multimodal applications, but evaluations often neglect abstract dimensions such as personality traits and human values. |
| Approach: | They propose a Visual Question Answering (VQA) benchmark based on Schwartz’s value dimensions that capture core human values guiding people’s preferences and actions. |
| Outcome: | The proposed model can be used to evaluate visual question answering (VQA) tasks and to simulate diverse personas. |
Aligning to Social Norms and Values in Interactive Narratives (2022.naacl-main)
Copied to clipboard
| Challenge: | Social value alignment is the ability to create agents that act in alignment with socially beneficial norms and values in interactive narratives or text-based games. |
| Approach: | They introduce a game-value ALignment agent that uses social commonsense to restrict its action space to actions that are aligned with socially beneficial values. |
| Outcome: | The proposed agent improves state-of-the-art task performance by 4% while reducing the frequency of socially harmful behaviors by 25% compared to strong contemporary value alignment approaches. |