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New benchmark dataset SURGE analyzes social media sentiment during events

By PulseAugur Editorial · [2 sources] ·

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

IMPACT Enables more nuanced analysis of public opinion and crisis response by incorporating social interaction structures.

RANK_REASON The cluster contains a research paper introducing a new benchmark dataset for social media analysis.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New benchmark dataset SURGE analyzes social media sentiment during events

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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Chen Su, Pengsen Cheng, Yuanhe Tian, Yan Song ·

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

    arXiv:2605.21198v1 Announce Type: cross Abstract: 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 …

  2. arXiv cs.AI TIER_1 English(EN) · 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 …

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