Feature selection for event discovery in social media: A comparative study. (October 2015)

• Record Type: Journal Article
• Authors: Zhao, Jie; Wang, Xueya; Jin, Peiquan
• Is Part Of: Computers in human behavior. Volume 51:Part B(2015)
• Page Start: 903
• Page End: 909
• Publication Date: 2015-10
• Subjects: Microblog -- Event discovery -- Feature selection -- Algorithm comparison; Interactive computer systems -- Periodicals; Man-machine systems -- Periodicals; 004.019
• DOI: 10.1016/j.chb.2014.11.007
• Languages: English
• ISSNs: 0747-5632

Abstract

Highlights: We analyze five feature selection methods for event discovery in social media. We present an improved feature selection method. We conduct comparative experiments on a real dataset using various metrics. We discuss the choosing of appropriate feature selection methods for microblogs. Abstract: Microblog as one kind of typical social media has many research implications in social event discovery and social-media-based e-learning and collaborative learning. At present, researchers usually employ feature-based classification approaches to detect social events in microblogs. However, it is very common to get different results when different features are used in event discovery. Therefore, it has been a critical issue how to select appropriate features for event discovery in microblogs. In this paper, we analyze five different feature selection methods and present an improved method for selecting features for microblog-based event discovery. We compare all the methods on a real microblog dataset in terms of various metrics including precision, recall, and F-measure. And finally we discuss the best feature selection method for the event discovery in microblogs. To the best of our knowledge, there are no such comparative studies on feature selection for event discovery in social media, and this paper is expected to offer some useful references for the future research and applications on the event discovery in microblogs.