Survey on Sentiment Analysis in Social Media

S. Ms, Hiroko Ms
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Abstract

Sentiment Analysis (SA) is a computational treatment of opinions and emotions. And it is the most active area of Natural Language Processing (NLP), Social Network Mining and Multimedia Data mining. Sentiment analysis can be done for decision making process like product reviews, stock marketing, political debates, news articles and election results prediction. The developing significance of sentiment analysis with the popularity of social network such as Facebook, Twitter, Instagram and Flicker. The users of the social media express their feelings with both text and visual content. Predicting emotion from textual is easy but with visual content is quite difficult so far. A visual content does not contain any objects, locations and actions but it has cues about emotions, sentiment. Sentiment analysis of huge scale visual content can help better extract user sentiment towards topics and events such as image tweets, GIFs, videos. In this paper we analyze various research based on role of sentiment analysis on social media and come out with the evaluation and efficiency of sentiment analysis.
社交媒体情感分析调查
情感分析(SA)是一种对观点和情绪的计算处理。它是自然语言处理(NLP)、社会网络挖掘和多媒体数据挖掘中最活跃的领域。情感分析可以用于产品评论、股票营销、政治辩论、新闻文章和选举结果预测等决策过程。随着Facebook、Twitter、Instagram、Flicker等社交网络的普及,情感分析的发展意义。社交媒体的用户通过文字和视觉内容来表达他们的感受。从文本中预测情感是很容易的,但从视觉内容中预测情感是相当困难的。视觉内容不包含任何物体、位置和动作,但它有关于情感和情绪的线索。大规模视觉内容的情感分析可以帮助更好地提取用户对主题和事件的情感,如图片推文、动图、视频。本文分析了基于情感分析在社交媒体中的作用的各种研究,得出了情感分析的评价和效率。
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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