Semantic Expansion of Tweet Contents for Enhanced Event Detection in Twitter

Date

2012-08-29

Author

Ozdikis, Ozer
Karagöz, Pınar
Oğuztüzün, Mehmet Halit S.

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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This paper aims to enhance event detection methods in a micro-blogging platform, namely Twitter. The enhancement technique we propose is based on lexico-semantic expansion of tweet contents while applying document similarity and clustering algorithms. Considering the length limitations and idiosyncratic spelling in Twitter environment, it is possible to take advantage of word similarities and to enrich texts with similar words. The semantic expansion technique we implement is based on syntagmatic and paradigmatic relationships between words, extracted from their co-occurrence statistics. As our technique does not depend on an existing ontology or a lexicon database such as WordNet, it should be applicable for any language. The proposed technique is applied on a tweet set collected for three days from the users in Turkey. The results indicate earlier detection of events and improvements in accuracy.

Subject Keywords

Event detection, Clustering, Micro-blogging, Twitter, Tweets in Turkish, Semantics, Word co-occurrences

URI

https://hdl.handle.net/11511/34327

DOI

https://doi.org/10.1109/asonam.2012.14

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

O. Ozdikis, P. Karagöz, and M. H. S. Oğuztüzün, “Semantic Expansion of Tweet Contents for Enhanced Event Detection in Twitter,” 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/34327.