P1SCO: Social Dimensions from a Perspectivist Lens

2026-05-24

AI Summary

This study addresses the need to systematically characterize the diversity of social interactions in social media comments and the mechanisms through which individual differences and platform-specific features shape these interactions. To this end, we construct a multi-platform comment dataset spanning three major platforms, annotated along ten social dimensions by human raters whose demographic profiles, Big Five personality traits, and political orientations are also collected as metadata. Through cross-platform data collection, multidimensional annotation, and hierarchical organization, this dataset uniquely enables the investigation of heterogeneity in social perception across multiple levels—comments, individuals, and platforms—providing a high-quality resource for exploring cutting-edge questions such as how annotator consistency, personality traits, and political stances influence social interpretation.

Abstract

We introduce P1SCO, a dataset of social media comments collected from three distinct platforms, annotated according to ten social dimensions to capture the diversity of social interactions and perceptions. The dataset is carefully disaggregated to allow analysis at the level of individual comments, annotators, and platforms. In addition to the social dimension labels, we include rich metadata on the annotators, including demographics, Big Five personality profiles, and political affiliation. This combination of comment-level annotations and annotator-level features enables nuanced analyses of how social perception varies across platforms, individual differences, and demographic factors. By preserving the diversity of annotator perspectives, our dataset supports studies of inter- and intra-annotator agreement, the influence of personality and political orientation on social interpretation, and the cross-platform dynamics of social discourse.

Problem

• social dimensions
• annotator perspectives
• social media comments
• individual differences
• cross-platform analysis

Innovation

• social dimensions
• perspectivist annotation
• cross-platform analysis
• annotator metadata
• personality and political affiliation