An Ensemble Based Approach for Sentiment Classification in Asian Regional Language  

作　　者：Mahesh B.Shelke Jeong Gon Lee Sovan Samanta Sachin N.Deshmukh G.Bhalke Daulappa Rahul B.Mannade Arun Kumar Sivaraman 

机构地区：[1]Department of Computer Science and Information Technology,Dr.Babasaheb Ambedkar Marathwada University,Aurangabad,Maharashtra,431004,India [2]Division of Applied Mathematics,Wonkwang University,460,Iksan daero,Iksan Si,Jeonbuk,54538,Korea [3]Department of Mathematics,Tamralipta Mahavidyalaya,Tamluk,West Bengal,721636,India [4]Department of Electronics and Telecommunication Engineering,AISSMSCOE,Pune,Maharashtra,411001,India [5]Department of Information Technology,Govemment College of Engineering,Aurangabad,Maharashtra,431005,India [6]School of Computer Science and Engineering,Vellore Institute of Technology,Chennai,600127,India

出　　处：《Computer Systems Science & Engineering》2023年第3期2457-2468,共12页计算机系统科学与工程（英文）

基　　金：This paper was supported by Wonkwang University in 2022.

摘　　要：In today’s digital world,millions of individuals are linked to one another via the Internet and social media.This opens up new avenues for information exchange with others.Sentiment analysis(SA)has gotten a lot of attention during the last decade.We analyse the challenges of Sentiment Analysis(SA)in one of the Asian regional languages known as Marathi in this study by providing a benchmark setup in which wefirst produced an annotated dataset composed of Marathi text acquired from microblogging websites such as Twitter.We also choose domain experts to manually annotate Marathi microblogging posts with positive,negative,and neutral polarity.In addition,to show the efficient use of the annotated dataset,an ensemble-based model for sentiment analysis was created.In contrast to others machine learning classifier,we achieved better performance in terms of accuracy for ensemble classifier with 10-fold cross-validation(cv),outcomes as 97.77%,f-score is 97.89%.

关 键 词：Sentiment analysis machine learning lexical resource ensemble classifier 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]