Semantic Expansion of Hashtags for Enhanced Event Detection in Twitter

Date

2012-09-09

Author

Özdikiş, Özer
Karagöz, Pınar
Oğuztüzün, Mehmet Halit Seyfullah

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In this work, we present an event detection method in Twitter based on clustering of hashtags and introduce an enhancement technique by using the semantic similarities between the hashtags. To this aim, we devised two methods for tweet vector generation and evaluated their effect on clustering and event detection performance in comparison to word-based vector generation methods. By analyzing the contexts of hashtags and their co-occurrence statistics with other words, we identify their paradigmatic relationships and similarities. We make use of this information while applying a lexico-semantic expansion on tweet contents before clustering the tweets based on their similarities. Our aim is to tolerate spelling errors and capture statements which actually refer to the same concepts. We evaluate our enhancement solution on a three-day dataset of tweets with Turkish content. In our evaluations, we observe clearer clusters, improvements in accuracy, and earlier event detection times.

Subject Keywords

Event Detection, Clustering, Twitter, Hashtags, Tweets in Turkish, Semantics, Word Co-occurrences

URI

https://hdl.handle.net/11511/70908
https://www.cs.ubc.ca/~welu/woss2012/papers/1-ozdikis.pdf

Conference Name

VLDB 2012 Workshop on Online Social Systems WOSS, August 31, 2012

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

Ö. Özdikiş, P. Karagöz, and M. H. S. Oğuztüzün, “Semantic Expansion of Hashtags for Enhanced Event Detection in Twitter,” presented at the VLDB 2012 Workshop on Online Social Systems WOSS, August 31, 2012, Istanbul, Turkey, 2012, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/70908.