Twitter情绪分析的有用功能 [英] Twitter Sentiments Analysis useful features
问题描述
我正在尝试实现情感分析功能,并寻找可以从推文消息中提取的有用功能.我现在脑海中的功能是:
I'm trying to implement Sentiments Analysis functionality and looking for useful features which can be extracted from tweet messages.The features which I have in my mind for now are:
- 情感词
- 情感图标
- 感叹号
- 否定词
- 强度词(非常,真的等)
此任务还有其他有用的功能吗?我的目标不仅是检测推文的正面还是负面,而且我还需要检测阳性或阴性的水平(假设范围是0到100).我们欢迎任何对印刷纸的输入或引用.
Is there any other useful features for this task? My goal is not only detect that tweet is positive or negative but also I need to detect level of positivity or negativity(let say in a scale from 0 to 100). Any inputs or references to printed papers are very welcome.
谢谢.
推荐答案
其他有用的方法是:
- 拉长的单词(例如goooood)
- 每个单词的字母和双字母组合(特别是如果您的语料库很大的话)
关于参考文献:克里斯托弗·波茨(Christopher Potts)撰写的本教程非常出色,而且很重要: http://sentiment.christopherpotts.net/
Regarding references: This tutorial by Christopher Potts is very good and to the point: http://sentiment.christopherpotts.net/
其他论文:
- Twitter是情感分析和观点挖掘的语料库.亚历山大·帕特里克(Patrick Paroubek)
- 使用远程监督的Twitter情感分类.Go等.2009.
- 在Twitter上从有偏数据和嘈杂数据中检测出强烈情绪.巴博萨和冯.2010.
- 非正式文本中的情感强度检测.Thelwall等.(2010).JAIST
- Twitter as a Corpus for Sentiment Analysis and Opinion Mining. Alexander Pak, Patrick Paroubek
- Twitter Sentiment Classification using Distant Supervision. Go et al. 2009.
- Robust Sentiment Detection on Twitter from Biased and Noisy Data. Barbosa and Feng. 2010.
- Sentiment strength detection in short informal text. Thelwall et al. (2010). JAIST
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