Event Detection in Twitter: Methodological Evaluation and Structural Analysis of the Bibliometric Data

Abstract

Twitter—a social networking service is increasingly becoming an important source of news and information for various aspects of our life. However, harnessing reliable sources is both tedious and challenging. Algorithms for mining and detecting events from Twitter have been developed. In this paper, event detection techniques are investigated. In essence, a theoretical comparison of the state-of-the-art event detection algorithms is performed along with highlights to the current issues and proper suggestions to mitigate them. In addition, a knowledge domain map analysis using CiteSpace is applied to the bibliometric data in the field in order to explore the structural dynamics of the research in this domain.