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However in this work we Footnote 5 helped facilitate further data preprocessing, feature extraction, and to compare with the text being classified to determine a.

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Table 4 summarises the hyperparameters and training settings used for these models, together with the evaluation results see the evaluation section for this discussion. The tweets in the dataset are analysed to see how many of the tweets are positive, negative or neutral according to the sentiment scores assigned by VADER. Particularly related to the context of this work, since the workshop Nakov et al.