Sensing real-world events using Arabic Twitter posts

Alsaedi, Nasser, Burnap, Peter ORCID: https://orcid.org/0000-0003-0396-633X and Rana, Omer Farooq ORCID: https://orcid.org/0000-0003-3597-2646 2016. Sensing real-world events using Arabic Twitter posts. Presented at: International AAAI Conference on Web and Social Media (ICWSM), Cologne, Germany, 17-20 May 2016. Proceedings of the Tenth International AAAI Conference on Web and Social Media (ICWSM 2016). AAAI, pp. 515-518.

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Abstract

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

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics Data Innovation Research Institute (DIURI)
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Publisher:	AAAI
Related URLs:	Organisation
Date of First Compliant Deposit:	2 August 2019
Last Modified:	01 Nov 2022 10:19
URI:	https://orca.cardiff.ac.uk/id/eprint/91040

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