Sentiment Analysis in Multiple Languages: A Review of Current Approaches and Challenges

Author:

Kumaresan C1,Thangaraju P1

Affiliation:

1. Bishop Heber College, Affiliated to Bharathidasan University, Trichy, India.

Abstract

Sentiment analysis, the process of automatically identifying and extracting subjective information from text, has gained increasing attention in recent years due to its potential applications in a variety of fields. However, the task of sentiment analysis can be challenging when applied to texts in multiple languages, as it requires not only language-specific preprocessing and feature extraction techniques, but also the development and adaptation of machine learning models that are able to handle the complexities of different languages. This research paper provides an overview of the current approaches and challenges in sentiment analysis for multiple languages. This study begins by discussing the general principles and techniques of sentiment analysis, including the use of deep learning and machine learning methods, as well as the importance of feature selection and ethical considerations. It examines the specific challenges and approaches for sentiment analysis in various languages, including Arabic, Chinese, Russian, and English. The use of multimodal sentiment analysis and the potential applications of sentiment analysis in various domains, such as healthcare, social media, and customer service. At the end, this review highlights the potential of sentiment analysis in multiple languages and the need for further research to improve the accuracy and reliability of sentiment analysis models for a variety of languages and domains. Future work should also address the ethical concerns involved in the collection and use of sentiment analysis data, as well as the challenges of adapting models to new languages and domains.

Publisher

REST Publisher

Subject

General Mathematics,General Physics and Astronomy,General Agricultural and Biological Sciences,General Environmental Science,General Medicine,Multidisciplinary,Nutrition and Dietetics,Medicine (miscellaneous),Insect Science,Physiology,Ecology, Evolution, Behavior and Systematics,Insect Science,Ecology, Evolution, Behavior and Systematics,General Physics and Astronomy,General Engineering,General Mathematics,General Agricultural and Biological Sciences,General Environmental Science,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3