Multilingual Twitter Sentiment Classification: The Role of Human Annotators

@article{Mozetic2016MultilingualTS,
  title={Multilingual Twitter Sentiment Classification: The Role of Human Annotators},
  author={I. Mozetic and Miha Grcar and Jasmina Smailovic},
  journal={PLoS ONE},
  year={2016},
  volume={11}
}
What are the limits of automated Twitter sentiment classification? We analyze a large set of manually labeled tweets in different languages, use them as training data, and construct automated classification models. It turns out that the quality of classification models depends much more on the quality and size of training data than on the type of the model trained. Experimental results indicate that there is no statistically significant difference between the performance of the top… Expand
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