Abstract
Microblogging has become a primary channel by which people not only share information, but also search for information. However, microblog search results are most often displayed by simple criteria such as creation time or author. A review of the literature suggests that clustering by topic may be useful, but short posts offer limited scope for clustering using lexical evidence alone. This paper therefore presents an approach to topical clustering based on augmenting lexical evidence with the use of Wikipedia as an external source of evidence for topical similarity. The main idea is to link terms in microblog posts to Wikipedia pages and then to leverage Wikipedia's link structure to estimate semantic similarity, Results show statistically significant relative improvements of about 3% in cluster purity using a relatively small (7500-post, 5-topic) Twitter test collection. Linking terms in microblog posts to Wikipedia pages is also shown to offer a useful basis for cluster labeling.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Proceedings of the American Society for Information Science and Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.