Trained models for multi-task multi-dataset learning for text classification in tweets
Cite this dataset:
Mishra, Shubhanshu (2019): Trained models for multi-task multi-dataset learning for text classification in tweets. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-1917934_V1
Use this persistent URL to link to this dataset:
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: https://github.com/socialmediaie/SocialMediaIE/blob/master/SocialMediaIE/scripts/multitask_multidataset_classification.py
See https://github.com/socialmediaie/SocialMediaIE and https://socialmediaie.github.io 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
Subject Social Sciences
Keywords twitter; deep learning; machine learning; trained models; multi-task learning; multi-dataset learning; sentiment; sarcasm; abusive content;
License CC BY
Corresponding Creator Shubhanshu Mishra
Downloaded 1929 times
Version DOI Comment Publication Date
1 10.13012/B2IDB-1917934_V1 2019-09-17
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