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New benchmark dataset SURGE analyzes social media event sentiment

Researchers have introduced SURGE, a new benchmark dataset designed to analyze social media sentiment dynamics around public events. SURGE organizes over 800,000 posts from 67 events across five categories into time-series data, preserving the interaction structure between posts. This benchmark aims to improve opinion forecasting and crisis response by enabling the study of how post interactions influence collective dynamics and event evolution. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Provides a new dataset for training and evaluating models in social media sentiment analysis and event forecasting.

RANK_REASON The cluster describes a new academic paper introducing a benchmark dataset for social media analysis. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

COVERAGE [1]

  1. arXiv cs.AI TIER_1 · Yan Song ·

    SURGE: An Event-Centric Social Media Sentiment Time Series Benchmark with Interaction Structure

    Public events on social media generate large volumes of discussion whose collective dynamics carry direct value for opinion forecasting and crisis response. Capturing how these dynamics evolve across an event's lifecycle requires organizing fragmented posts into event-level time …