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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 26 / No. 1: Twenty-Sixth AAAI Conference on Artificial Intelligence

ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback

March 8, 2023

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Authors

Yuheng Hu

Arizona State University


Ajita John

Avaya Labs


Fei Wang

IBM T. J. Watson Research Lab


Subbarao Kambhampati

Arizona State University


DOI:

10.1609/aaai.v26i1.8106


Abstract:

During broadcast events such as the Superbowl, the U.S. Presidential and Primary debates, etc., Twitter has become the de facto platform for crowds to share perspectives and commentaries about them. Given an event and an associated large-scale collection of tweets, there are two fundamental research problems that have been receiving increasing attention in recent years. One is to extract the topics covered by the event and the tweets; the other is to segment the event. So far these problems have been viewed separately and studied in isolation. In this work, we argue that these problems are in fact inter-dependent and should be addressed together. We develop a joint Bayesian model that performs topic modeling and event segmentation in one unified framework. We evaluate the proposed model both quantitatively and qualitatively on two large-scale tweet datasets associated with two events from different domains to show that it improves significantly over baseline models.

Topics: AAAI

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HOW TO CITE:

Yuheng Hu|| Ajita John|| Fei Wang|| Subbarao Kambhampati ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback Proceedings of the AAAI Conference on Artificial Intelligence, 26 (2012) 59.

Yuheng Hu|| Ajita John|| Fei Wang|| Subbarao Kambhampati ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback AAAI 2012, 59.

Yuheng Hu|| Ajita John|| Fei Wang|| Subbarao Kambhampati (2012). ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback. Proceedings of the AAAI Conference on Artificial Intelligence, 26, 59.

Yuheng Hu|| Ajita John|| Fei Wang|| Subbarao Kambhampati. ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback. Proceedings of the AAAI Conference on Artificial Intelligence, 26 2012 p.59.

Yuheng Hu|| Ajita John|| Fei Wang|| Subbarao Kambhampati. 2012. ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback. "Proceedings of the AAAI Conference on Artificial Intelligence, 26". 59.

Yuheng Hu|| Ajita John|| Fei Wang|| Subbarao Kambhampati. (2012) "ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback", Proceedings of the AAAI Conference on Artificial Intelligence, 26, p.59

Yuheng Hu|| Ajita John|| Fei Wang|| Subbarao Kambhampati, "ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback", AAAI, p.59, 2012.

Yuheng Hu|| Ajita John|| Fei Wang|| Subbarao Kambhampati. "ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback". Proceedings of the AAAI Conference on Artificial Intelligence, 26, 2012, p.59.

Yuheng Hu|| Ajita John|| Fei Wang|| Subbarao Kambhampati. "ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback". Proceedings of the AAAI Conference on Artificial Intelligence, 26, (2012): 59.

Yuheng Hu|| Ajita John|| Fei Wang|| Subbarao Kambhampati. ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback. AAAI[Internet]. 2012[cited 2023]; 59.


ISSN: 2374-3468


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