1 code implementation • 21 Apr 2021 • Soroosh Tayebi Arasteh, Mehrpad Monajem, Vincent Christlein, Philipp Heinrich, Anguelos Nicolaou, Hamidreza Naderi Boldaji, Mahshad Lotfinia, Stefan Evert
As a strong baseline, we propose a two-stage DL-based method: first, we create automatically labeled training data by applying a standard sentiment classifier to tweet replies and aggregating its predictions for each original tweet; our rationale is that individual errors made by the classifier are likely to cancel out in the aggregation step.
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Tweet-Reply Sentiment Analysis
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