Automatic Identification and Classification of Bragging in Social Media

Mali Jin, Daniel Preotiuc-Pietro, A. Seza Doğruöz, Nikolaos Aletras


Abstract
Bragging is a speech act employed with the goal of constructing a favorable self-image through positive statements about oneself. It is widespread in daily communication and especially popular in social media, where users aim to build a positive image of their persona directly or indirectly. In this paper, we present the first large scale study of bragging in computational linguistics, building on previous research in linguistics and pragmatics. To facilitate this, we introduce a new publicly available data set of tweets annotated for bragging and their types. We empirically evaluate different transformer-based models injected with linguistic information in (a) binary bragging classification, i.e., if tweets contain bragging statements or not; and (b) multi-class bragging type prediction including not bragging. Our results show that our models can predict bragging with macro F1 up to 72.42 and 35.95 in the binary and multi-class classification tasks respectively. Finally, we present an extensive linguistic and error analysis of bragging prediction to guide future research on this topic.
Anthology ID:
2022.acl-long.273
Volume:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
May
Year:
2022
Address:
Dublin, Ireland
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3945–3959
Language:
URL:
https://aclanthology.org/2022.acl-long.273
DOI:
10.18653/v1/2022.acl-long.273
Bibkey:
Cite (ACL):
Mali Jin, Daniel Preotiuc-Pietro, A. Seza Doğruöz, and Nikolaos Aletras. 2022. Automatic Identification and Classification of Bragging in Social Media. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 3945–3959, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Automatic Identification and Classification of Bragging in Social Media (Jin et al., ACL 2022)
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