Sensing Real-World Events Using Arabic Twitter Posts

Authors

  • Nasser Alsaedi Cardiff University
  • Pete Burnap Cardiff University
  • Omer Rana Cardiff University

DOI:

https://doi.org/10.1609/icwsm.v10i1.14765

Abstract

In recent years, there has been increased interest in eventdetection using data posted to social media sites. Automaticallytransforming user-generated content into informationrelating to events is a challenging task due to the short informallanguage used within the content and the variety oftopics discussed on social media. Recent advances in detectingreal-world events in English and other languages havebeen published. However, the detection of events in the Arabiclanguage has been limited to date. To address this task, wepresent an end-to-end event detection framework which comprisessix main components: data collection, pre-processing,classification, feature selection, topic clustering and summarization.Large-scale experiments over millions of ArabicTwitter messages show the effectiveness of our approach fordetecting real-world event content from Twitter posts.

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Published

2021-08-04

How to Cite

Alsaedi, N., Burnap, P., & Rana, O. (2021). Sensing Real-World Events Using Arabic Twitter Posts. Proceedings of the International AAAI Conference on Web and Social Media, 10(1), 515-518. https://doi.org/10.1609/icwsm.v10i1.14765