A crossed-domain sentiment analysis system for the discovery of current careers from social networks

@inproceedings{Anh2014ACS,
  title={A crossed-domain sentiment analysis system for the discovery of current careers from social networks},
  author={Trinh Thi Van Anh and Hoang Xuan Dau},
  booktitle={SoICT},
  year={2014}
}
In recent years, the sentiment analysis on data messages from social networks has attracted high attention of researchers. However, most of their works have been focused on classifying user messages to positive (or like) and negative (or dislike) on social issues or discussion topics. In addition, they usually only worked with English messages from a single data source, or a domain. In this paper, we proposed a crossed-domain sentiment analysis system for the discovery of current careers from… CONTINUE READING

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Key Quantitative Results

  • The performance results of the proposed system are promising for crossed-domain sentiment analysis, with the precision of over 85% and the recall of over 90%.

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