#One paper per week# Anger Is More Influential than Joy: Sentiment Correlation in Weibo
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论文题目:Anger Is More Influential than Joy: Sentiment Correlation in Weibo
论文地址:http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0110184#pone-0110184-g007
作为我的第一篇认真看完的论文,这短短的8页纸,可谓花了不少时间。首先是单词的问题,论文里面有不少的专业词汇,让我几乎要每读一句话就要查一次词典。其次是知识的匮乏,太多的原理,式子,分析方法都是自己以前完全没见过的。不过,读完后,确实是学到了不少作者们的amazing ideas。
回归正文:
正如题目所说的,这篇文章就是在大家的微博中发现一个有趣的观点:愤怒比高兴容易在网络传播。
1、作者通过抓取2010年12月到2011年2月的weibo,大概有7000万条,作为原始数据。
2、接下来需要对weibo进行情感分类,可以用LIWC( Linguistic Inquiry and Word Count )来进行emotion classfication,但由于LIWC只能区分positive和negative,所以作者自己找出并使用了50个常见情感词来建立一个贝叶斯分类器,最后把情感分为了4类:anger, joy, disgust, sadness。
3、使用了pearson correlation以及spearman correlation来处理情感传递的关系。结果发现anger的相互关系程度更大一些,所以得出题目的结论。
另外,该作者团队还上线了一个“心情搜索”的应用,网址是:http://xinqings.nlsde.buaa.edu.cn/index.php
以上均为个人见解,因本人水平有限,如发现有所错漏,敬请指出,谢谢!
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