A method for detecting local events using the spatiotemporal locality of microblog posts

Abstract

Purpose

The purpose of this paper is to propose a method to detect local events in real time using Twitter, an online microblogging platform. The authors especially aim at detecting local events regardless of the type and scale.

Design/methodology/approach

The method is based on the observation that relevant tweets (Twitter posts) are simultaneously posted from the place where a local event is happening. Specifically, the method first extracts the place where and the time when multiple tweets are posted using a hierarchical clustering technique. It next detects the co-occurrences of key terms in each spatiotemporal cluster to find local events. To determine key terms, it computes the term frequency-inverse document frequency (TFIDF) scores based on the spatiotemporal locality of tweets.

Findings

From the experimental results using geotagged tweet data between 9 a.m. and 3 p.m. on October 9, 2011, the method significantly improved the precision of between 50 and 100 per cent at the same recall compared to a baseline method.

Originality/value

In contrast to existing work, the method described in this paper can detect various types of small-scale local events as well as large-scale ones by incorporating the spatiotemporal feature of tweet postings and the text relevance of tweets. The findings will be useful to researchers who are interested in real-time event detection using microblogs.

Citation

Sugitani, T., Shirakawa, M., Hara, T. and Nishio, S. (2015), "A method for detecting local events using the spatiotemporal locality of microblog posts", International Journal of Web Information Systems, Vol. 11 No. 1, pp. 2-16. https://doi.org/10.1108/IJWIS-04-2014-0017