Cooooooooooooooollllllllllllll!!!!!!!!!!!!!! Using Word Lengthening to Detect Sentiment in Microblogs

We present an automatic method which lever-ages word lengthening to adapt a sentiment lexicon specifically for Twitter and similar so-cial messaging networks. The contributions of the paper are as follows. First, we call at-tention to lengthening as a widespread phe-nomenon in microblogs and social messag-ing, and demonstrate the importance of han-dling it correctly. We then show that lengthen-ing is strongly associated with subjectivity and sentiment. Finally, we present an automatic method which leverages this association to de-tect domain-specific sentiment- and emotion-bearing words. We evaluate our method by comparison to human judgments, and analyze its strengths and weaknesses. Our results are of interest to anyone analyzing sentiment in microblogs and social networks, whether for research or commercial purposes.