Datasets of the article "From Classification to Quantification in Tweet Sentiment Analysis"

Datasets used for the following SNAM paper:
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Title: From Classification to Quantification in Tweet Sentiment Analysis
Authors: Wei Gao and Fabrizio Sebastiani
Organization: Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar
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[Content]

* SemEval2013, SemEval2014, SemEval2015 datasets:
  - semeval.train.feature.txt: Training set for learning sentiment models at development stage
  - semeval.dev.feature.txt: Held-out set for tuning parameters
  - semeval.train+dev.feature.txt: Training set for learning the final sentiment model
  - semeval13.test.feature.txt: SemEval2013 test set
  - semeval14.test.feature.txt: SemEval2014 test set
  - semeval15.test.feature.txt: SemEval2015 test set
  
* Other datasets: semeval2016, sanders, sst, omd, hcr, gasp, wa, wb
  - X.train.feature.txt: Training set for learning sentiment models at development stage
  - X.dev.feature.txt: Held-out set for tuning parameters
  - X.train+dev.feature.txt: Training set for learning the final sentiment model
  - X.test.feature.txt (or X.dev-test.feature.txt for semeval2016 only): Test set
where X is one of semeval2016, sanders, sst, omd, hcr and gasp.

* Training files are saved in ./data/train directory, and held-out and test files are in ./data/test directory

For more details, please refer to the paper.

[Citation]
You can cite the following paper when referring to the dataset:

@article{gao2016classification,
  title={From classification to quantification in tweet sentiment analysis},
  author={Gao, Wei and Sebastiani, Fabrizio},
  journal={Social Network Analysis and Mining},
  volume={6},
  number={1},
  pages={19},
  year={2016},
  publisher={Springer}
}