Sentiment mining: An approach for Bengali and Tamil tweets

SudhaShanker Prasad, J. Kumar, D. Prabhakar, S. Tripathi
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引用次数: 13

Abstract

This paper presents a proposed work for extracting the sentiments from tweets in Indian Language. We proposed a system that deal with the goal to extract the sentiments from Bengali & Tamil tweets. Our aim is to classify a given Bengali or Tamil tweets into three sentiment classes namely positive, negative or neutral. In recent time, Twitter gain much attention to NLP researchers as it is most widely used platform that allows the user to share there opinion in form of tweets. The proposed methodology used unigram and bi-gram models along with different supervised machine learning techniques. We also consider the use of features generated from lexical resources such as Wordnets and Emoticons Tagger.
情感挖掘:孟加拉语和泰米尔语推文的一种方法
本文提出了一种从印度语推文中提取情感的方法。我们提出了一个系统来处理从孟加拉语和泰米尔语推文中提取情感的目标。我们的目标是将给定的孟加拉语或泰米尔语推文分为三种情绪类别,即积极,消极或中性。最近一段时间,Twitter获得了NLP研究人员的关注,因为它是最广泛使用的平台,允许用户以tweet的形式分享他们的观点。提出的方法使用单图和双图模型以及不同的监督机器学习技术。我们还考虑使用词汇资源生成的特征,如Wordnets和Emoticons Tagger。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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