Classifying sentiment in microblogs: is brevity an advantage?

@article{Bermingham2010ClassifyingSI,
  title={Classifying sentiment in microblogs: is brevity an advantage?},
  author={Adam Bermingham and Alan F. Smeaton},
  journal={Proceedings of the 19th ACM international conference on Information and knowledge management},
  year={2010}
}
  • A. Bermingham, A. Smeaton
  • Published 2010
  • Computer Science
  • Proceedings of the 19th ACM international conference on Information and knowledge management
Microblogs as a new textual domain offer a unique proposition for sentiment analysis. Their short document length suggests any sentiment they contain is compact and explicit. However, this short length coupled with their noisy nature can pose difficulties for standard machine learning document representations. In this work we examine the hypothesis that it is easier to classify the sentiment in these short form documents than in longer form documents. Surprisingly, we find classifying sentiment… Expand

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