Sentiment Manifestation of Kannada Tweets

S. B, Adithya S Nair, Anirudh D Shasthry, Atishay Sg, Disha R
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Abstract

In the current world scenario, Internet has become a major platform for online learning, exchanging ideas and sharing opinions. Social networking sites like Twitter, Facebook, Instagram are rapidly gaining popularity as they allow people to share and express their views about topics, have discussion with different communities, or post messages across the world. The main goal of sentiment analysis is to detect and analyse attitude, opinions or sentiments in the text. Sentiment analysis has reached its popularity by extracting knowledge from huge amount data present online. The Process of analysis includes selecting features and opinion which is a challenging task in languages other than English. In this project, we have targeted one of the most promising and widely used social media platform- Twitter where opinions are shared as “Tweets”. We have specifically chosen the tweets made in Kannada and analyse the sentiment of those tweets. Kannada is a Dravidian language spoken majorly in the south Indian state of Karnataka, with minorities in all neighboring states. Emotion analysis is the method of defining and evaluating the emotions conveyed in textual data. Emotion detection and classification are straightforward tasks that can be completed based on the emotions conveyed in the text, such as fear, rage, happiness, sorrow, affection, motivation, or neutral.
卡纳达语推文的情感表现
在当今世界,互联网已经成为在线学习、交流思想和分享意见的主要平台。像Twitter、Facebook、Instagram这样的社交网站正迅速流行起来,因为它们允许人们分享和表达他们对话题的看法,与不同的社区进行讨论,或者在世界各地发布消息。情感分析的主要目的是发现和分析文本中的态度、观点或情绪。情感分析通过从大量在线数据中提取知识而变得流行。分析的过程包括选择特征和观点,这在英语以外的语言中是一项具有挑战性的任务。在这个项目中,我们的目标是最有前途和最广泛使用的社交媒体平台之一——Twitter,在Twitter上,人们以“tweet”的形式分享观点。我们特别选择了用卡纳达语发的推文,并分析了这些推文的情绪。卡纳达语是一种主要在印度南部卡纳塔克邦使用的德拉威语,在所有邻近的邦都有少数人使用。情感分析是对文本数据中所表达的情感进行定义和评价的方法。情绪检测和分类是一项简单的任务,可以根据文本中传达的情绪来完成,比如恐惧、愤怒、快乐、悲伤、情感、动机或中立。
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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