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The added value of auxiliary data in sentiment analysis of Facebook posts

Matthijs Meire (UGent) , Michel Ballings (UGent) and Dirk Van den Poel (UGent)
(2016) DECISION SUPPORT SYSTEMS. 89. p.98-112
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Keywords
CLASSIFIERS, SOCIAL MEDIA, PREDICTION, ENSEMBLE, Facebook, Text mining, Sentiment analysis, Machine learning, Social media, SUPPORT VECTOR MACHINES, CLASSIFICATION LEARNING ALGORITHMS

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Citation

Please use this url to cite or link to this publication:

MLA
Meire, Matthijs, Michel Ballings, and Dirk Van den Poel. “The Added Value of Auxiliary Data in Sentiment Analysis of Facebook Posts.” DECISION SUPPORT SYSTEMS 89 (2016): 98–112. Print.
APA
Meire, Matthijs, Ballings, M., & Van den Poel, D. (2016). The added value of auxiliary data in sentiment analysis of Facebook posts. DECISION SUPPORT SYSTEMS, 89, 98–112.
Chicago author-date
Meire, Matthijs, Michel Ballings, and Dirk Van den Poel. 2016. “The Added Value of Auxiliary Data in Sentiment Analysis of Facebook Posts.” Decision Support Systems 89: 98–112.
Chicago author-date (all authors)
Meire, Matthijs, Michel Ballings, and Dirk Van den Poel. 2016. “The Added Value of Auxiliary Data in Sentiment Analysis of Facebook Posts.” Decision Support Systems 89: 98–112.
Vancouver
1.
Meire M, Ballings M, Van den Poel D. The added value of auxiliary data in sentiment analysis of Facebook posts. DECISION SUPPORT SYSTEMS. 2016;89:98–112.
IEEE
[1]
M. Meire, M. Ballings, and D. Van den Poel, “The added value of auxiliary data in sentiment analysis of Facebook posts,” DECISION SUPPORT SYSTEMS, vol. 89, pp. 98–112, 2016.
@article{8081908,
  author       = {Meire, Matthijs and Ballings, Michel and Van den Poel, Dirk},
  issn         = {0167-9236},
  journal      = {DECISION SUPPORT SYSTEMS},
  keywords     = {CLASSIFIERS,SOCIAL MEDIA,PREDICTION,ENSEMBLE,Facebook,Text mining,Sentiment analysis,Machine learning,Social media,SUPPORT VECTOR MACHINES,CLASSIFICATION LEARNING ALGORITHMS},
  language     = {eng},
  pages        = {98--112},
  title        = {The added value of auxiliary data in sentiment analysis of Facebook posts},
  url          = {http://dx.doi.org/10.1016/j.dss.2016.06.013},
  volume       = {89},
  year         = {2016},
}

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