首页> 外文会议>ASE/IEEE International Conference on Social Computing >A :) Is Worth a Thousand Words: How People Attach Sentiment to Emoticons and Words in Tweets
【24h】

A :) Is Worth a Thousand Words: How People Attach Sentiment to Emoticons and Words in Tweets

机译:A :)胜过千言万语:人们如何将情绪与Tweets中的表情符号和词语相连

获取原文

摘要

Emoticons are widely used to express positive or negative sentiment on Twitter. We report on a study with live users to determine whether emoticons are used to merely emphasize the sentiment of tweets, or whether they are the main elements carrying the sentiment. We found that the sentiment of an emoticon is in substantial agreement with the sentiment of the entire tweet. Thus, emoticons are useful as predictors of tweet sentiment and should not be ignored in sentiment classification. However, the sentiment expressed by an emoticon agrees with the sentiment of the accompanying text only slightly better than random. Thus, using the text accompanying emoticons to train sentiment models is not likely to produce the best results, a fact that we show by comparing lexicons generated using emoticons with others generated using simple textual features.
机译:表情符号广泛用于表达Twitter上的积极或负面情绪。我们向实时用户报告学习,以确定表情符号是否仅用于强调推文的情绪,或者它们是携带情绪的主要元素。我们发现,与整个推文的情绪相当大的协议,表情符号的情绪。因此,表情符号是有用的推文情绪的预测因子,并且在情绪分类中不应忽略。然而,由表情符号表示的情感同意伴随文本的情绪略高于随机。因此,使用伴随表情符号培训情绪模型的文本不太可能产生最佳结果,这是我们通过将使用与使用简单文本特征生成的其他人生成的词典进行比较来表明。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号