TweetNLP: Cutting-Edge Natural Language Processing for Social Media

Jose Camacho-collados, Kiamehr Rezaee, Talayeh Riahi, Asahi Ushio, Daniel Loureiro, Dimosthenis Antypas, Joanne Boisson, Luis Espinosa Anke, Fangyu Liu, Eugenio Martínez Cámara

Abstract
In this paper we present TweetNLP, an integrated platform for Natural Language Processing (NLP) in social media. TweetNLP supports a diverse set of NLP tasks, including generic focus areas such as sentiment analysis and named entity recognition, as well as social media-specific tasks such as emoji prediction and offensive language identification. Task-specific systems are powered by reasonably-sized Transformer-based language models specialized on social media text (in particular, Twitter) which can be run without the need for dedicated hardware or cloud services. The main contributions of TweetNLP are: (1) an integrated Python library for a modern toolkit supporting social media analysis using our various task-specific models adapted to the social domain; (2) an interactive online demo for codeless experimentation using our models; and (3) a tutorial covering a wide variety of typical social media applications.
Anthology ID:
2022.emnlp-demos.5
Volume:
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Month:
December
Year:
2022
Address:
Abu Dhabi, UAE
Editors:
Wanxiang Che, Ekaterina Shutova
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
38–49
Language:
URL:
https://aclanthology.org/2022.emnlp-demos.5
DOI:
10.18653/v1/2022.emnlp-demos.5
Bibkey:
Cite (ACL):
Jose Camacho-collados, Kiamehr Rezaee, Talayeh Riahi, Asahi Ushio, Daniel Loureiro, Dimosthenis Antypas, Joanne Boisson, Luis Espinosa Anke, Fangyu Liu, and Eugenio Martínez Cámara. 2022. TweetNLP: Cutting-Edge Natural Language Processing for Social Media. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 38–49, Abu Dhabi, UAE. Association for Computational Linguistics.
Cite (Informal):
TweetNLP: Cutting-Edge Natural Language Processing for Social Media (Camacho-collados et al., EMNLP 2022)
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PDF:
https://preview.aclanthology.org/naacl-24-ws-corrections/2022.emnlp-demos.5.pdf
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