Affiliation:
1. Shanxi University of Finance and Economics, Shanxi Key Laboratory of Economic Big Data, Taiyuan, China
2. Shanxi University, Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Taiyuan, China
Abstract
Traditional methods for sentiment analysis, when applied in a monolingual context, often yield less than optimal results in multilingual settings. This underscores the need for a more thorough exploration of cross-lingual sentiment analysis (CLSA) methodologies to improve analytical effectiveness. CLSA, confronted with obstacles such as linguistic disparities and a lack of resources, seeks to evaluate sentiments across a range of languages. First, the research background, challenges, existing solution ideas, and evaluation tasks of CLSA are summarized. Subsequently, new perspectives including different granularity levels, machine translation support, and sentiment transfer strategies perspectives are highlighted. Finally, potential avenues for future research are discussed.
Publisher
Association for Computing Machinery (ACM)
Reference174 articles.
1. Mohamed Abdalla and Graeme Hirst. 2017. Cross-lingual sentiment analysis without (good) translation. In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP, 2017 Volume 1: Long Papers). Asian Federation of Natural Language Processing, 506–515. Retrieved from https://www.aclweb.org/anthology/I17-1051
2. Mohamed Abdel-Hady, Riham Mansour, and Ahmed Ashour. 2014. Cross-lingual Twitter polarity detection via projection across word-aligned corpora. In Proceedings of the International Conference on Machine Learning Conference and Workshop on Issues of Sentiment Discovery and Opinion Mining(ICML WISDOM 2014). 1–12. Retrieved from https://www.sentic.net/wisdom2014mansour.pdf
3. Borrow from rich cousin: transfer learning for emotion detection using cross lingual embedding
4. Solving Data Sparsity for Aspect Based Sentiment Analysis Using
Cross-Linguality and Multi-Linguality
5. Persian Sentiment Analysis Without Training Data Using Cross-Lingual Word Embeddings
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