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—User generated content on Twitter (produced at an enormous rate of 340 million tweets per day) provides a rich source for gleaning people's emotions, which is necessary for deeper understanding of people's behaviors and actions. Extant studies on emotion identification lack comprehensive coverage of " emotional situations " because they use relatively(More)
The problem of automatic extraction of sentiment expressions from informal text, as in microblogs such as tweets is a recent area of investigation. Compared to formal text, such as in product reviews or news articles , one of the key challenges lies in the wide diversity and informal nature of sentiment expressions that cannot be trivially enumerated or(More)
Cursing is not uncommon during conversations in the physical world: 0.5% to 0.7% of all the words we speak are curse words, given that 1% of all the words are first-person plural pronouns (e.g., we, us, our). On social media, people can instantly chat with friends without face-to-face interaction, usually in a more public fashion and broadly disseminated(More)
In domain-specific search systems, knowledge of a domain of interest is embedded as a backbone that guides the search process. But the knowledge used in most such systems 1. exists only for few well known broad domains; 2. is of a basic nature: either purely hierarchical or involves only few relationship types; and 3. is not always kept up-to-date missing(More)
Existing studies on predicting election results are under the assumption that all the users should be treated equally. However, recent work [14] shows that social media users from different groups (e.g., " silent majority " vs. " vocal minority ") have significant differences in the generated content and tweeting behavior. The effect of these differences on(More)
Many research studies adopt manually selected patterns for semantic relation extraction. However, manually identifying and discovering patterns is time consuming and it is difficult to discover all potential candidates. Instead, we propose an automatic pattern construction approach to extract verb synonyms and antonyms from English newspapers. Instead of(More)
We propose an approach for ranking microblog search results. The basic idea is to leverage user engagement for the purpose of ranking: if a microblog post received many retweets/replies, this means users find it important and it should be ranked higher. However, simply applying the raw count of engagement may bias the ranking by favoring posts from(More)
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