V alue S cope: Unveiling Implicit Norms and Values via Return Potential Model of Social Interactions (2024)

Abstract: 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 confirming that even closely related communities exhibit remarkably diverse norms. This diversity supports existing theories and adds a new dimension to understanding community interactions. ValueScope not only delineates differences in social norms but also effectively tracks 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.

## introduction social norms-the perceived, informal, and mostly unwritten rules that govern acceptable behaviors within a community-are foundational to understanding the dynamics of social interactions and shaping the community's identity @xcite . social values, in turn, are the deeper ideals and principles that a community aspires to uphold, guiding the creation and enforcement of these norms @xcite . social norms and values emerge organically through the interplay of behaviors @xcite and are difficult to grasp without gaining experience of the community firsthand. this complexity poses challenges for new users to ## methodology we introduce valuescope-a theoreticallygrounded framework to model social norms and values in online communities ( §3.1). this framework is operationalized through a modeling pipeline con-sisting of a normness scale predictor ( §3.2) and a community preference predictor ( §3.3) to capture two interwoven dimensions of community values. ## experiments we outline our data curation process ( §4.1) and describe experiments done to thoroughly validate the normness scale predictor ( §4.2) and the community preference predictor ( §4.3). ## results using the validated nsp and cpp, we explore prevailing norms and values of online communities by modeling return potentials and analyzing the point of maximum return (pmr) and potential return difference (prd) to corroborate our findings with existing work on similar communities and then uncover additional insights at scale. return potential modeling (rpm) our rpm results demonstrate how a community's preferences varies with the scale of normness. we highlight two key rpm plots-formality preferences in politics subreddits and supportiveness preferences in science subreddits-to validate valuescope in figure 3 (with full results in appendix m). in the politics subreddits, community preference for formal to neutral comments is nearly invariant, but as comments become progressively more casual, there is a steep decrease in preference across all subreddits. these patterns align with community rules that encourage more formal interactions (e.g., "quality control" and "no disinformation") and denounce casual behaviors (e.g., "no trolling" and "no spamming"). higher preferences toward formal comments in r/libertarian is consistent with its strict guidelines encouraging detailed explanations and references to policies. the rpm results of science subreddits show a general disapproval for toxic behaviors that gradually changes to approval as the comments become supportive. r/askscience and r/asksciencediscussion-subreddits designated for scientific discussion with guidelines discouraging offensive language and encouraging helpful answers-show a stronger preference for supportive comments than r/shittyaskscience, which is a parody created to mock r/askscience @xcite . overall, valuescope effectively surfaces community norms shaped by guidelines and core premises. ## analysis to address rq2-can we predict the change in norms based on observed normative behaviors?we study the fluidity and stability of social norms and its implications using valuescope and social science theories, specifically norm intensity and crystallization @xcite , then analyze their temporal changes in the context of external events and internal community conflicts. norm crystallization social norms are constantly evolving. understanding such changes and their predictive features can help community moderators respond effectively. @xcite introduces the concepts of norm intensity (n i) and crystallization (cr). n i measures the magnitude of community (dis)approval of behaviors at a given normness scale, indicating how strongly the community cares about the norm, while cr represents the level of consensus on the preference. taking the year 2021 as a cutoff, we test the predictive power of n i and cr on upcoming temporal changes (t c := ∆n i) with a linear regression model. we use results from valuescope predictions and follow implementation defined in @xcite (details in appendix k). our results in ## conclusion & future directions we introduced valuescope, a novel framework based on the rpm theory from social science, to quantify social norms and values at scale. we comprehensively validated the effectiveness of val-uescope to assess the normness of behaviors and predict community preferences while controlling for confounders. valuescope enables numerous quantitative analyses, including predicting norm shifts and contextualizing temporal changes with external events, providing a deeper understanding of social norm dynamics in online communities. our work contributes a robust and generalizable method that can be easily extended to various norms and communities. it opens up many exciting possibilities for applications and future research: computational modeling applications our framework can enhance community moderation tools by integrating theoretically grounded insights, such as maximum return potential, to refine toxicity detectors. it can also guide generation models to produce contextually appropriate responses specialized to each community's unique norms. applications for social scientists our method empowers the development of new hypotheses about social norms, by providing social scientists with enhanced tools to explore how norms form and influence social interactions within communities. support tools for communities valuescope can enhance community management by enabling moderators to monitor and address norm shifts in real-time. it can help transform widely accepted but informal norms into explicit rules, clarifying guidelines and easing new member integration. this approach is applicable in various settings (e.g., workplaces) where it can guide individuals on appropriate cultural expressions, improving their integration and acceptance. platform developers can use this method to refine community recommendation engines, aligning users with groups that match their preferences and values, thereby enhancing user engagement and community growth.