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- Title
A survey of recent methods on deriving topics from Twitter: algorithm to evaluation.
- Authors
Nugroho, Robertus; Paris, Cecile; Nepal, Surya; Yang, Jian; Zhao, Weiliang
- Abstract
In recent years, studies related to topic derivation in Twitter have gained a lot of interest from businesses and academics. The interconnection between users and information has made social media, especially Twitter, an ultimate platform for propagation of information about events in real time. Many applications require topic derivation from this social media platform. These include, for example, disaster management, outbreak detection, situation awareness, surveillance, and market analysis. Deriving topics from Twitter is challenging due to the short content of the individual posts. The environment itself is also highly dynamic. This paper presents a review of recent methods proposed to derive topics from social media platform from algorithms to evaluations. With regard to algorithms, we classify them based on the features they exploit, such as content, social interactions, and temporal aspects. In terms of evaluations, we discuss the datasets and metrics generally used to evaluate the methods. Finally, we highlight the gaps in the research this far and the problems that remain to be addressed.
- Subjects
SITUATIONAL awareness; EMERGENCY management; ALGORITHMS; MARKETING research; SOCIAL interaction; SOCIAL media; SOCIAL media in education
- Publication
Knowledge & Information Systems, 2020, Vol 62, Issue 7, p2485
- ISSN
0219-1377
- Publication type
Article
- DOI
10.1007/s10115-019-01429-z