What's with the attitude? a study of participant attitude in multi-party online discussions

Mining sentiment from user generated content is a very important task in Natural Language
Processing. An example of such content is threaded discussions which act as a very important tool for communication and collaboration in the Web. Threaded discussions include e-mails, e-mail lists, bulletin boards, newsgroups, and Internet forums. Most of the work on sentiment analysis has been centered
around ?nding the sentiment toward products or topics. In this work, we present a method to identify the attitude of participants in an online discussion toward one another. This would enable us to build a signed network representation of participant interaction where every edge has a sign that indicates whether the interaction is positive or negative. This is different from most of the research on social networks that has focused almost exclusively on positive links. The method is experimentally tested using a manually labeled set
of discussion posts. The results show that the
proposed method is capable of identifying attitudinal sentences, and their signs, with high
accuracy and that it outperforms several other
baselines.