Papers by Wafia Adouane

2 papers
Identifying Sentiments in Algerian Code-switched User-generated Comments (2020.lrec-1)

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Challenge: a recent study has focused on sentiment analysis for the Arabic variety, but it has been extended to other domains.
Approach: They build a corpus of 36,000 code-switched user-generated comments annotated for sentiments in Algerian Arabic.
Outcome: The proposed model performs better on unedited code-switched and unbalanced data across sentiment classes.
Normalising Non-standardised Orthography in Algerian Code-switched User-generated Data (D19-55)

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Challenge: a new corpus of unstructured data from social media is presenting challenges to NLP research . standardisation is neither natural nor universal, it is rather a human invention.
Approach: They compile a parallel corpus of Arabic textual data matched with human annotations . they use a deep neural model designed to deal with context-dependent spelling correction .
Outcome: The proposed model performs best with two CNN sub-network encoders and an LSTM decoder . pre-processing data token-by-token with edit-distance aligner significantly improves performance .

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