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A Process for Exploring Employees’ Relationships via Social Network and Sentiment Analysis

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Data Mining and Big Data (DMBD 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10387))

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Abstract

The proposed study is to analyze and visualize properties of the social network constructed from a dataset based on Enron mail dataset, and utilize sentiment analysis as an additional source of information to study employees’ relationships in a company. We concluded that when social network analysis is used in conjunction with emotion detection, it is possible to see the positive or negative areas where the company must work to promote a healthy organizational culture and uncover possible organizational issues in a timely manner.

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Acknowledgment

This research was supported in part by the Ministry of Science and Technology, Taiwan, under the Grant MOST 103-2221-E-007-073-MY3.

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Authors and Affiliations

  1. Institute of Information Systems and Applications, National Tsing Hua University, Hsinchu, Taiwan

    Jeydels Barahona

  2. Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan

    Hung-Min Sun

  3. Research Center for Information Technology Innovation, Academia Sinica, Taipei, Taiwan

    Hung-Min Sun

Authors
  1. Jeydels Barahona
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  2. Hung-Min Sun
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Corresponding author

Correspondence to Hung-Min Sun .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Kyushu University, Fukuoka, Japan

    Hideyuki Takagi

  3. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

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Barahona, J., Sun, HM. (2017). A Process for Exploring Employees’ Relationships via Social Network and Sentiment Analysis. In: Tan, Y., Takagi, H., Shi, Y. (eds) Data Mining and Big Data. DMBD 2017. Lecture Notes in Computer Science(), vol 10387. Springer, Cham. https://doi.org/10.1007/978-3-319-61845-6_1

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  • DOI: https://doi.org/10.1007/978-3-319-61845-6_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61844-9

  • Online ISBN: 978-3-319-61845-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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