A Comparative Study on Word Embeddings and Social NLP Tasks

Fatma Elsafoury, Steven R. Wilson, Naeem Ramzan


Abstract
In recent years, gray social media platforms, those with a loose moderation policy on cyberbullying, have been attracting more users. Recently, data collected from these types of platforms have been used to pre-train word embeddings (social-media-based), yet these word embeddings have not been investigated for social NLP related tasks. In this paper, we carried out a comparative study between social-media-based and non-social-media-based word embeddings on two social NLP tasks: Detecting cyberbullying and Measuring social bias. Our results show that using social-media-based word embeddings as input features, rather than non-social-media-based embeddings, leads to better cyberbullying detection performance. We also show that some word embeddings are more useful than others for categorizing offensive words. However, we do not find strong evidence that certain word embeddings will necessarily work best when identifying certain categories of cyberbullying within our datasets. Finally, We show even though most of the state-of-the-art bias metrics ranked social-media-based word embeddings as the most socially biased, these results remain inconclusive and further research is required.
Anthology ID:
2022.socialnlp-1.5
Volume:
Proceedings of the Tenth International Workshop on Natural Language Processing for Social Media
Month:
July
Year:
2022
Address:
Seattle, Washington
Editors:
Lun-Wei Ku, Cheng-Te Li, Yu-Che Tsai, Wei-Yao Wang
Venue:
SocialNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
55–64
Language:
URL:
https://aclanthology.org/2022.socialnlp-1.5
DOI:
10.18653/v1/2022.socialnlp-1.5
Bibkey:
Cite (ACL):
Fatma Elsafoury, Steven R. Wilson, and Naeem Ramzan. 2022. A Comparative Study on Word Embeddings and Social NLP Tasks. In Proceedings of the Tenth International Workshop on Natural Language Processing for Social Media, pages 55–64, Seattle, Washington. Association for Computational Linguistics.
Cite (Informal):
A Comparative Study on Word Embeddings and Social NLP Tasks (Elsafoury et al., SocialNLP 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.socialnlp-1.5.pdf
Video:
 https://aclanthology.org/2022.socialnlp-1.5.mp4
Code
 efatmae/comparative_analysis_word_embeddings_on_social_nlp_tasks