Trained models for multi-task multi-dataset learning for text classification in tweets

  • Shubhanshu Mishra (Creator)

Dataset

Description

Trained models for multi-task multi-dataset learning for text classification in tweets.
Classification tasks include sentiment prediction, abusive content, sarcasm, and veridictality.

Models were trained using: <a href="https://github.com/socialmediaie/SocialMediaIE/blob/master/SocialMediaIE/scripts/multitask_multidataset_classification.py">https://github.com/socialmediaie/SocialMediaIE/blob/master/SocialMediaIE/scripts/multitask_multidataset_classification.py</a>
See <a href="https://github.com/socialmediaie/SocialMediaIE">https://github.com/socialmediaie/SocialMediaIE</a> and <a href="https://socialmediaie.github.io">https://socialmediaie.github.io</a> for details.

If you are using this data, please also cite the related article:
Shubhanshu Mishra. 2019. Multi-dataset-multi-task Neural Sequence Tagging for Information Extraction from Tweets. In Proceedings of the 30th ACM Conference on Hypertext and Social Media (HT '19). ACM, New York, NY, USA, 283-284. DOI: https://doi.org/10.1145/3342220.3344929
Date made availableSep 17 2019
PublisherUniversity of Illinois Urbana-Champaign

Keywords

  • deep learning
  • trained models
  • multi-dataset learning
  • multi-task learning
  • machine learning
  • twitter
  • sentiment
  • sarcasm
  • abusive content

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