A survey of recent methods on deriving topics from Twitter: algorithm to evaluation

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. Man...

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Bibliographic Details
Published in:Knowledge and information systems 2020-07, Vol.62 (7), p.2485-2519
Main Authors: Nugroho, Robertus, Paris, Cecile, Nepal, Surya, Yang, Jian, Zhao, Weiliang
Format: Article
Language:English
Subjects:
Algorithms
Computer Science
Data Mining and Knowledge Discovery
Database Management
Derivation
Digital media
Disaster management
Evaluation
Information Storage and Retrieval
Information Systems and Communication Service
Information Systems Applications (incl.Internet)
IT in Business
Situational awareness
Social factors
Social networks
Survey Paper
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Summary: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.
ISSN:0219-1377
0219-3116
DOI:10.1007/s10115-019-01429-z