用NLP分析社交媒体，提前预警冲突爆发
NLP Case Study on Predicting the Before and After of the Ukraine-Russia and Hamas-Israel Conflicts
- 对比冲突前后社交平台文本特征变化
- 预测毒性等语言属性误差仅1.2%
- 适合政策制定与危机预警研究者
本文提出一种基于自然语言处理（NLP）的方法，用于预测乌克兰-俄罗斯和哈马斯-以色列冲突前后社交媒体中的文本毒性及其他属性。研究从推特和Reddit收集两场冲突前后的数据集，并进行分阶段分析。结果表明：(1) 冲突前后社交媒体讨论存在显著差异；(2) 推特、Reddit等平台的语言表达可有效预示潜在冲突。通过先进的监督与非监督NLP技术，对冲突前后语言属性的预测误差低至约1.2%，为未来冲突的风险识别与防范提供了可行路径。
原文摘要 · Abstract (English)
We propose a method to predict toxicity and other textual attributes through the use of natural language processing (NLP) techniques for two recent events: the Ukraine-Russia and Hamas-Israel conflicts. This article provides a basis for exploration in future conflicts with hopes to mitigate risk through the analysis of social media before and after a conflict begins. Our work compiles several datasets from Twitter and Reddit for both conflicts in a before and after separation with an aim of predicting a future state of social media for avoidance. More specifically, we show that: (1) there is a noticeable difference in social media discussion leading up to and following a conflict and (2) social media discourse on platforms like Twitter and Reddit is useful in identifying future conflicts before they arise. Our results show that through the use of advanced NLP techniques (both supervised and unsupervised) toxicity and other attributes about language before and after a conflict is predictable with a low error of nearly 1.2 percent for both conflicts.
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