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A Socio-Semantic Network Analysis of Discourse Using the Network Lifetime and the Moving Stanza Window Method

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Advances in Quantitative Ethnography (ICQE 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1112))

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Abstract

This study proposes a new temporal Socio-Semantic Network Analysis (SSNA) of discourse by using the network lifetime and the moving stanza window method to analyze idea improvement in learning as knowledge-creation. The procedure of our proposed method has four steps. The first step entails making a discourse analysis unit. One discourse analysis unit is composed of discourses depending on the set numbers at a size of the moving stanza window method. The second step is calculating the total value of degree centrality for each discourse analysis unit with periods of the network lifetime by using SSNA. The third step involves calculating the difference value between discourse analysis units to define the candidates for the pivotal points. The last step is tracing the discourse back from the candidates for the pivotal points to identify segments for in-depth dialogical discourse analysis. To evaluate the proposed method, we analyzed discourse data in collaborative learning using different methods with and without the network lifetime and moving stanza window. As a result, new pivotal points were detected by implementing both the network lifetime and the moving stanza window method. An in-depth dialogical discourse analysis of a new pivotal discourse segment confirmed the appropriateness of the detection. Based on the results, it is concluded that our proposed method is better in detecting pivotal points of learning as knowledge-creation compared to the previous approach.

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Acknowledgements

This work was supported by JSPS KAKENHI Grant Numbers 16H0187, JP18K13238, 19H01715.

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Authors and Affiliations

  1. Advanced Institute of Industrial Technology, 1-10-40, Higashi-Ooi, Shinagawa-ku, Tokyo, 1400022, Japan

    Ayano Ohsaki

  2. Research and Education Center for the Learning Sciences, Shizuoka University, 836 Ohya, Suruga-ku, Shizuoka-Shi, Shizuoka, 4228529, Japan

    Ayano Ohsaki & Jun Oshima

Authors
  1. Ayano Ohsaki
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  2. Jun Oshima
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Correspondence to Ayano Ohsaki .

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Editors and Affiliations

  1. University of Wisconsin–Madison, Madison, WI, USA

    Brendan Eagan

  2. University of Copenhagen, Copenhagen, Denmark

    Morten Misfeldt

  3. University of Wisconsin–Madison, Madison, WI, USA

    Amanda Siebert-Evenstone

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Ohsaki, A., Oshima, J. (2019). A Socio-Semantic Network Analysis of Discourse Using the Network Lifetime and the Moving Stanza Window Method. In: Eagan, B., Misfeldt, M., Siebert-Evenstone, A. (eds) Advances in Quantitative Ethnography. ICQE 2019. Communications in Computer and Information Science, vol 1112. Springer, Cham. https://doi.org/10.1007/978-3-030-33232-7_29

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  • DOI: https://doi.org/10.1007/978-3-030-33232-7_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33231-0

  • Online ISBN: 978-3-030-33232-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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