Webis: An Ensemble for Twitter Sentiment Detection

@inproceedings{Hagen2015WebisAE,
  title={Webis: An Ensemble for Twitter Sentiment Detection},
  author={Matthias Hagen and Martin Potthast and Michel B{\"u}chner and Benno Stein},
  booktitle={SemEval@NAACL-HLT},
  year={2015}
}
We reproduce four Twitter sentiment classification approaches that participated in previous SemEval editions with diverse feature sets. The reproduced approaches are combined in an ensemble, averaging the individual classifiers’ confidence scores for the three classes (positive, neutral, negative) and deciding sentiment polarity based on these averages. The experimental evaluation on SemEval data shows our re-implementations to slightly outperform their respective originals. Moreover, not too… CONTINUE READING
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