Hot topic detection and evaluation of multi-relation effects-Reference-Cited by-同舟云学术

Hot topic detection and evaluation of multi-relation effects

Published:2021-11-08 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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Author:

Zirbilek Nadir Emre¹,Erakin Mustafa²,Özyer Tansel³,Alhajj Reda⁴

Affiliation:

1. University of Calgary, Alberta, Canada

2. TOBB University, Ankara, Turkey

3. Istanbul Medipol University, Istanbul, Turkey

4. University of Southern Denmark, Odense, Denmark

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3487351.3490972

Reference19 articles.

1. Ishikawa , S. , Arakawa , Y. , Tagashira , S. , & Fukuda , A. ( 2012 , February). Hot topic detection in local areas using Twitter and Wikipedia . In ARCS 2012 (pp. 1--5). IEEE. Ishikawa, S., Arakawa, Y., Tagashira, S., & Fukuda, A. (2012, February). Hot topic detection in local areas using Twitter and Wikipedia. In ARCS 2012 (pp. 1--5). IEEE.

2. Detecting hot topics from Twitter: A multiview approach

3. Identification of Trending Topics Using Periodically Collected Twitter Data: Ranjini V 7 (3.12) (2018) 205--208 Identification of Trending Topics Using Periodically Collected Twitter Data: Ranjini V 7 (3.12) (2018) 205--208

4. Jónsson E. & Stolee J. An Evaluation of Topic Modelling Techniques for Twitter. Jónsson E. & Stolee J. An Evaluation of Topic Modelling Techniques for Twitter.

5. Empirical study of topic modeling in Twitter

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