Neural networks for sentiment analysis on Twitter

B. Duncan, Yanqing Zhang
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引用次数: 52

Abstract

The online medium has become a significant way that people express their opinions online. Sentiment analysis can be used to find out the polarity of an opinion, such as positive, negative, or neutral. Sentiment analysis has applications such as companies getting their customer's opinions on their products, political sentiment analysis, or opinions on movie reviews. Recent research has involved looking at text from online blogs, tweets, online movie reviews, etc. to try and classify the text as being positive, negative, or neutral. For this research, a feedforward neural network will be experimented with for sentiment analysis of tweets. The training set of tweets are collected using the Twitter API using positive and negative keywords. The testing set of tweets are collected using the same positive and negative keywords.
推特情感分析的神经网络
网络媒体已经成为人们在线表达意见的重要方式。情感分析可以用来找出观点的极性,比如积极的、消极的或中立的。情感分析的应用包括公司获取客户对其产品的意见、政治情绪分析或对电影评论的意见。最近的研究包括查看在线博客、推特、在线电影评论等文本,试图将文本分为积极、消极或中性。在本研究中,将实验前馈神经网络用于tweet的情感分析。使用Twitter API使用positive和negative关键字收集tweet的训练集。使用相同的正面和负面关键字收集tweet的测试集。
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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