TweetNLP: Cutting-Edge Natural Language Processing for Social Media

• URL: http://arxiv.org/abs/2206.14774v1
• Date: Wed, 29 Jun 2022 17:16:58 GMT
• Title: TweetNLP: Cutting-Edge Natural Language Processing for Social Media
• Authors: Jose Camacho-Collados and Kiamehr Rezaee and Talayeh Riahi and Asahi Ushio and Daniel Loureiro and Dimosthenis Antypas and Joanne Boisson and Luis Espinosa-Anke and Fangyu Liu and Eugenio Mart\'inez-C\'amara and Gonzalo Medina and Thomas Buhrmann and Leonardo Neves and Francesco Barbieri
• Abstract summary: TweetNLP is an integrated platform for Natural Language Processing (NLP) in social media. It supports a diverse set of NLP tasks, including generic focus areas such as sentiment analysis and named entity recognition. System is powered by reasonably-sized Transformer-based language models specialized on social media text.
• Score: 22.6980150693332
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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