Pandya A., Oussalah M., Kostakos P., Fatima U. (2020) MaTED: Metadata-Assisted Twitter Event Detection System. In: Lesot MJ. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2020. Communications in Computer and Information Science, vol 1237. Springer, Cham. https://doi.org/10.1007/978-3-030-50146-4_30
MaTED : metadata-assisted Twitter event detection system
|Author:||Pandya, Abhinay1; Oussalah, Mourad2; Kostakos, Panos1;|
1Center for Ubiquitous Computing, Faculty of ITEE, University of Oulu, Finland
2Center for Machine Vision and Signal Analysis, Faculty of ITEE, University of Oulu, Finland
|Online Access:||PDF Full Text (PDF, 0.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2022022420746
|Publish Date:|| 2022-02-24
Due to its asynchronous message-sharing and real-time capabilities, Twitter offers a valuable opportunity to detect events in a timely manner. Existing approaches for event detection have mainly focused on building a temporal profile of named entities and detecting unusually large bursts in their usage to signify an event. We extend this line of research by incorporating external knowledge bases such as DBPedia, WordNet; and exploiting specific features of Twitter for efficient event detection. We show that our system utilizing temporal, social, and Twitter-specific features yields improvement in the precision, recall, and DERate on the benchmarked Events2012 corpus compared to the state-of-the-art approaches.
Communications in computer and information science
|Pages:||402 - 414|
Information Processing and Management of Uncertainty in Knowledge-Based Systems. 18th International Conference, IPMU 2020, Lisbon, Portugal, June 15–19, 2020, Proceedings, Part I
|Host publication editor:||
Reformat, Marek Z.
Carvalho, João Paulo
International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work is partly supported by EU YoungRes project (#823701) on polarization detection.
© Springer Nature Switzerland AG 2020. “This is a post-peer-review, pre-copyedit version of an article published in Communications in Computer and Information Science. The final authenticated version is available online at https://doi.org/10.1007/978-3-030-50146-4_30.