Optimizing N-gram based text feature selection in sentiment analysis for commercial products in Twitter through polarity lexicons

Mark Anthony Cabanlit, Kurt Junshean Espinosa. Optimizing N-gram based text feature selection in sentiment analysis for commercial products in Twitter through polarity lexicons. In Nikolaos G. Bourbakis, George A. Tsihrintzis, Maria Virvou, editors, IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications, Chania, Crete, Greece, July 7-9, 2014. pages 94-97, IEEE, 2014. [doi]

@inproceedings{CabanlitE14,
  title = {Optimizing N-gram based text feature selection in sentiment analysis for commercial products in Twitter through polarity lexicons},
  author = {Mark Anthony Cabanlit and Kurt Junshean Espinosa},
  year = {2014},
  doi = {10.1109/IISA.2014.6878767},
  url = {http://dx.doi.org/10.1109/IISA.2014.6878767},
  researchr = {https://researchr.org/publication/CabanlitE14},
  cites = {0},
  citedby = {0},
  pages = {94-97},
  booktitle = {IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications, Chania, Crete, Greece, July 7-9, 2014},
  editor = {Nikolaos G. Bourbakis and George A. Tsihrintzis and Maria Virvou},
  publisher = {IEEE},
}