Abstract
Currently, social media platforms become a valuable source of user-defined multi-features and multimedia data. Such data could be used for several event related applications, such as event detection, event relationship identification, and event representation in the form of nodes and edges. In this paper, we use a systematic critical review to assess recent works in event related problems to understand the state-of-the-art. Specifically, we mainly focus on the following recent major research issues: (i) event definition and the concept behind the 5W1H dimensions from social media perspective; (ii) event detection, including social media data representation, dimensions similarity measures, datasets, and evaluation measures used in the event detection task; (iii) event relationships identification covering the current approaches for three categories of event relationships: temporal, spatial, and semantic; and (iv) event-based knowledge graph construction in which details about event graph components and approaches used in the event graph are described. Furthermore, we provide applications, challenges, findings for each question, and promising research directions.
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Notes
SVM is a supervised learning method used for classification.
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Mohammed, S., Getahun, F. & Chbeir, R. Events management in social media: a systematic literature review. Soc. Netw. Anal. Min. 13, 70 (2023). https://doi.org/10.1007/s13278-023-01079-8
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DOI: https://doi.org/10.1007/s13278-023-01079-8