Modeling heterogeneous networks for information ranking, enrichment and resolution on microblogs

Abstract

Microblogging, a new type of online information sharing platform through short messages of up to 140 characters, has grown up quickly and received increasing attentions in recent years. A microblogging platform (e.g., Twitter) enables both individuals and organizations to disseminate information, from current affairs to breaking news in a timely fashion, which makes it a valuable knowledge source with super-fresh information. For example, during Hurricane Irene in 2011, updates from users living in New York City and transportation/evacuation posts from the government are very useful information for people to keep track of the disaster. Therefore, conducting related Natural Language Processing (NLP) research on this new genre is demanded to assist knowledge mining and discovery.