IMPACTeen: Intentions, Manipulation, Persuasion, Annotations, and Consequences in Teen Communication Dataset

2026-06-15

AI Summary

This study addresses the scarcity of multi-perspective annotated data on social influence in adolescent contexts, which hinders effective detection and analysis of persuasive or manipulative behaviors. The authors present a bilingual (Polish/English) dataset comprising 1,021 texts and 5,100 annotations, uniquely developed through a collaborative annotation framework involving adolescents, parents, psychologists, communication experts, and teachers. The dataset spans interpersonal, media, and digital scenarios and captures multidimensional information including influence tactics, intent, and consequences. Initial annotations were generated using a constrained large language model and refined through a two-stage human validation process to ensure authenticity and semantic coverage. This resource enables research on social influence identification, inter-annotator disagreement analysis, cross-lingual modeling, and language model evaluation, offering a critical foundation for advancing studies on adolescent digital communication safety.

Abstract

IMPACTeen is a dataset of textual social influence scenarios spanning interpersonal, media-based, and digital settings in an adolescent context. It contains 1,021 texts, 5,100 individual annotation records, and gold labels for social influence techniques, with each text annotated from five distinct perspectives: teenagers, parents, psychologists, communication experts, and teachers. The resource was constructed through constrained LLM generation, followed by a two-step human editing and validation phase aimed at ensuring youth-context realism. A multi-dimensional annotation covered influence presence, techniques, intentions, consequences, resistance, reactions, and annotation confidence. The dataset supports research on social influence detection, annotator disagreement, cross-lingual modeling, and the training and evaluation of language models. The dataset was created in Polish and is accompanied by a corresponding English version.

Problem

• social influence
• teen communication
• annotation disagreement
• language modeling
• youth context

Innovation

• constrained LLM generation
• multi-perspective annotation
• youth-context realism
• social influence detection
• cross-lingual dataset