sentiment sensing：多语言情感动态的对比分析框架

Sentiment sensing: comparative analysis of multilingual sentiment dynamics

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研究者提出 sentiment sensing 框架，通过整合成分数据分析、函数型数据方法和非参数推断，解决跨国情感分析中语言偏差、成分数据约束和时间动态缺乏检验框架三大问题。该框架已在两个案例研究中测试，分析欧盟 27 国关于能源和人工智能的新闻文章。

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Abstract:Cross-country sentiment analysis faces three fundamental challenges: language-specific biases distort comparisons, compositional data constraints invalidate standard statistics and temporal dynamics lack rigorous testing frameworks. We introduce sentiment sensing, a framework that addresses these gaps through integrated statistical methods. By combining compositional data analysis, functional data methods, and non-parametric inference, sentiment sensing enables valid multilingual comparisons and statistically defensible detection of sentiment shifts. Our framework has been tested in two case studies, analyzing news articles from the 27 countries of the European Union on the topics of energy and artificial intelligence. Sentiment sensing focuses on multilingual sentiment analysis enabling rigorous comparative science.

Subjects:	Computation and Language (cs.CL); Applications (stat.AP)
Cite as:	arXiv:2611.01348 [cs.CL]
	(or arXiv:2611.01348v1 [cs.CL] for this version)
	https://doi.org/10.48550/arXiv.2611.01348 arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Elisa Di Nuovo [view email]
[v1] Sat, 31 Oct 2026 23:34:38 UTC (6,191 KB)

来源：arXiv cs.CL · arxiv.org