Understand
In this paper we propose four deep recurrent architectures to tackle the task of offensive tweet detection as well as further classification into targeting and subject of said targeting.
- Our architectures are based on LSTMs and GRUs, we present a simple bidirectional LSTM as a baseline system and then further increase the complexity of the models by adding convolutional layers and implementing a split-process-merge architecture with LSTM and GRU as processors.
- Multiple pre-processing techniques were also investigated.
- The validation F1-score results from each model are presented for the three subtasks as well as the final F1-score performance on the private competition test set.
Built on
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Bidirectional recurrent neural networks
Mike Schuster and Kuldip K Paliwal. 1997 · 1997
Earlier work this paper cites.
Nltk: The natural language toolkit
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Earlier work this paper cites.
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Later among the works it cites.
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Closest in time.
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