Abstract
Abstract: In this research, we introduce TweetNLP, a platform for social media Natural Language Processing (NLP). An extensive range of NLP tasks are supported by TweetNLP, including standard focus areas like sentiment analysis and named entity recognition as well as social media-specific tasks like emoticon prediction and offensive language detection. Task-specific systems run on moderately small Transformer-based language models that are focused on social media text, particularly Twitter, and don't require specialized hardware or cloud services to operate. TweetNLP's major contributions are: (1) an integrated Python library for a contemporary toolkit supporting social media analysis using various task-specific models tailored to the social domain; (2) an interactive online demo for codeless experimentation using our models; and (3) a tutorial covering a wide range of typical social media applications.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal for Research in Applied Science and Engineering Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
