TikStance: A Multimodal and Hierarchical Dataset for Multi-target Stance Analysis in TikTok Political Conversations
Merged summary
TL;DR - TikStance is a new multimodal, context-aware TikTok dataset for multi-target political stance detection, pairing 161 host videos with hierarchical comment trees to enable analysis grounded in both audiovisual and conversational context.
- Contains 161 videos and 13,876 comments centered on three 2024 U.S. election figures (Trump, Biden, Harris), collected September 2023–January 2025.
- Each discussion unit links a host video plus metadata to a parent-linked comment tree, supporting video-to-target and comment-to-target stance analysis.
- Labeled by three annotators on a three-class scheme (Favor, Against, None), with disagreements re-annotated; Krippendorff's α reached 0.743 (Trump), 0.723 (Biden), 0.722 (Harris).
- Descriptive analysis shows target-dependent stance distributions and conversational depth, with nested replies making up 23.3% of comments.
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TikStance: A Multimodal and Hierarchical Dataset for Multi-target Stance Analysis in TikTok Political Conversations
TL;DR - TikStance is a new multimodal, context-aware TikTok dataset for multi-target political stance detection, pairing 161 host videos with hierarchical comment trees to enable analysis grounded in both audiovisual and conversational context.
- Contains 161 videos and 13,876 comments centered on three 2024 U.S. election figures (Trump, Biden, Harris), collected September 2023–January 2025.
- Each discussion unit links a host video plus metadata to a parent-linked comment tree, supporting video-to-target and comment-to-target stance analysis.
- Labeled by three annotators on a three-class scheme (Favor, Against, None), with disagreements re-annotated; Krippendorff's α reached 0.743 (Trump), 0.723 (Biden), 0.722 (Harris).
- Descriptive analysis shows target-dependent stance distributions and conversational depth, with nested replies making up 23.3% of comments.