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Chinese National Conference on Social Media Processing

SMP 2014: Social Media Processing pp 206–219Cite as

From Post to Values: Mining Schwartz Values of Individuals from Social Media

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 489))

Abstract

This paper aims to provide a novel method called Automatic Estimation of Schwartz Values (AESV) from social media, which automatically conducts text categorization based on Schwartz theory. AESV comprises three key components: training, feature extraction and values computation. Specifically, a training corpus is firstly built from the Web for each Schwartz value type and the feature vector is then extracted by using Chi statistics. Last but most important, as for individual values calculation, the personal posts are collected as input data which are converted to a word vector. The similarities between input vector and each value feature vector are used to calculate the individual value priorities. An experiment with 101 participants has been conducted, implying that AESV could obtain the competitive results, which are close to manually measurement by expert survey. In a further experiment, 92 users with different patterns on Sina weibo are tested, indicating that AESV algorithm is robust and could be widely applied in surveying the values for a huge amount of people, which is normally expensive and time-consuming in social science research. It is noted that our work is promising to automatically measure individual’s values just using his/her posts on social media.

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Author information

Authors and Affiliations

  1. School of Software Engineering, Beijing Institute of Technology, Beijing, 100081, China

    Mengshu Sun & Jianyun Shang

  2. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

    Huaping Zhang

  3. School of Management and Economics, Beijing Institute of Technology, Beijing, China

    Yanping Zhao

Authors
  1. Mengshu Sun
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  2. Huaping Zhang
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  3. Yanping Zhao
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  4. Jianyun Shang
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Editor information

Editors and Affiliations

  1. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

    Heyan Huang

  2. Department of Computer Science and Technology, Harbin Institute of Technology, China

    Ting Liu

  3. Beijing Institute of Technology School of Computer Science, China

    Hua-Ping Zhang

  4. Department of Computer Science and Technology, Tsinghua University, China

    Jie Tang

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© 2014 Springer-Verlag Berlin Heidelberg

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Sun, M., Zhang, H., Zhao, Y., Shang, J. (2014). From Post to Values: Mining Schwartz Values of Individuals from Social Media. In: Huang, H., Liu, T., Zhang, HP., Tang, J. (eds) Social Media Processing. SMP 2014. Communications in Computer and Information Science, vol 489. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45558-6_19

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  • DOI: https://doi.org/10.1007/978-3-662-45558-6_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45557-9

  • Online ISBN: 978-3-662-45558-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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