Social media collect and spread on the Web personal opinions, facts, fake news and all kind
of information users may be interested in. Applying argument mining methods to such …

Sentiment analysis allows the semantic evaluation of pieces of text according to the
expressed sentiments and opinions. While considerable attention has been given to the …

Determining when conversational participants agree or disagree is instrumental for broader
conversational analysis; it is necessary, for example, in deciding when a group has reached …

On June 23rd 2016, UK held the referendum which ratified the exit from the EU. While most
of the traditional pollsters failed to forecast the final vote, there were online systems that hit …

We present a corpus that encompasses the complete history of conversations between
contributors to Wikipedia, one of the largest online collaborative communities. By recording …

Debate and deliberation play essential roles in politics and government, but most models
presume that debates are won mainly via superior style or agenda control. Ideally, however …

Computational approaches to opinion mining have mostly focused on polarity detection of
product reviews by classifying the given text as positive, negative or neutral. While, there is …

Stance detection is an important task, supporting many downstream tasks such as discourse
parsing and modeling the propagation of fake news, rumors, and science denial. In this …

To ease the difficulty of argument stance classification, the task of same side stance
classification (S3C) has been proposed. In contrast to actual stance classification, which …

Multi-target stance detection in tweets aims to detect the stance of given texts towards a
specific target entity. Most existing models on stance detection consider word embedding as …