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As the rapid growth of online social media attracts a large number of Internet users, the large volume of content generated by these users also provides us with an opportunity to study the lexical variation of people of different ages. In this paper, we present a latent variable model that jointly models the lexical content of tweets and Twitter users’(More)
Social networks are an important class of networks that span a wide variety of media, ranging from social websites such as Facebook and Google Plus, citation networks of academic papers and patents, caller networks in telecommunications, and hyperlinked document collections such as Wikipedia - to name a few. Many of these social networks now exceed millions(More)
Owing to the fast-responding nature and extreme success of social media, many companies resort to social media sites for monitoring the reputation of their brands and the opinions of the general public. To help companies in monitoring their brands, in this work, we delve into the task of extracting representative aspects and posts from users’ freetext posts(More)
In this paper we study how to summarize travel-related information in forum threads to generate supplementary travel guides. Such summaries presumably can provide additional and more up-to-date information to tourists. Existing multi-document summarization methods have limitations for this task because (1) they do not generate structured summaries but(More)
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