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: | Schools > Computer Science & Informatics Research Institutes & Centres > 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: | |
| 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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