Evaluation of Thematic Coherence in Microblogs

Iman Munire Bilal, Bo Wang, Maria Liakata, Rob Procter, Adam Tsakalidis


Abstract
Collecting together microblogs representing opinions about the same topics within the same timeframe is useful to a number of different tasks and practitioners. A major question is how to evaluate the quality of such thematic clusters. Here we create a corpus of microblog clusters from three different domains and time windows and define the task of evaluating thematic coherence. We provide annotation guidelines and human annotations of thematic coherence by journalist experts. We subsequently investigate the efficacy of different automated evaluation metrics for the task. We consider a range of metrics including surface level metrics, ones for topic model coherence and text generation metrics (TGMs). While surface level metrics perform well, outperforming topic coherence metrics, they are not as consistent as TGMs. TGMs are more reliable than all other metrics considered for capturing thematic coherence in microblog clusters due to being less sensitive to the effect of time windows.
Anthology ID:
2021.acl-long.530
Volume:
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
6800–6814
Language:
URL:
https://aclanthology.org/2021.acl-long.530
DOI:
10.18653/v1/2021.acl-long.530
Bibkey:
Cite (ACL):
Iman Munire Bilal, Bo Wang, Maria Liakata, Rob Procter, and Adam Tsakalidis. 2021. Evaluation of Thematic Coherence in Microblogs. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 6800–6814, Online. Association for Computational Linguistics.
Cite (Informal):
Evaluation of Thematic Coherence in Microblogs (Bilal et al., ACL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.acl-long.530.pdf
Video:
 https://aclanthology.org/2021.acl-long.530.mp4
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