Do language families matter? Evaluating LLMs for sentiment analysis through a hierarchical cross-lingual lens
Social media sentiment analysis has become one of the most significant instruments for understanding the opinion of the population in the spheres of healthcare, politics, and education. Yet, large language models (LLMs) remain unevenly distributed in their linguistic coverage, failing to adequately serve a large portion of the world's languages. This study evaluates five state-of-the-art LLMs: GPT-4o, Gemini 2.0 Flash, DeepSeek-V3, Mistral Large, and Claude 3.7 Sonnet on three-class sentiment cl
Record details
Published: 24 July 2026
Source: Frontiers in Artificial Intelligence
Category: Research
Topics: Healthcare · Children & education
Retrieved: 25 July 2026
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How to cite this record
ethics.ai (24 July 2026), “Do language families matter? Evaluating LLMs for sentiment analysis through a hierarchical cross-lingual lens,” evidence record 13183, https://ethics.ai/record/13183 (originally published by Frontiers in Artificial Intelligence).
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