• Computer Science
  • Published in ArXiv 2020

Adapting Deep Learning for Sentiment Classification of Code-Switched Informal Short Text

@article{Shakeel2020AdaptingDL,
  title={Adapting Deep Learning for Sentiment Classification of Code-Switched Informal Short Text},
  author={Muhammad Haroon Shakeel and Asim Karim},
  journal={ArXiv},
  year={2020},
  volume={abs/2001.01047}
}
Nowadays, an abundance of short text is being generated that uses nonstandard writing styles influenced by regional languages. Such informal and code-switched content are under-resourced in terms of labeled datasets and language models even for popular tasks like sentiment classification. In this work, we (1) present a labeled dataset calledMultiSenti for sentiment classification of codeswitched informal short text, (2) explore the feasibility of adapting resources from a resource-rich language… CONTINUE READING

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