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Incorporating Sentiment Analysis with Epistemic Network Analysis to Enhance Discourse Analysis of Twitter Data

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Advances in Quantitative Ethnography (ICQE 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1312))

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Abstract

While there has been much growth in the use of microblogging platforms (e.g., Twitter) to share information on a range of topics, researchers struggle to analyze the large volumes of data produced on such platforms. Established methods such as Sentiment Analysis (SA) have been criticized over their inaccuracy and limited analytical depth. In this exploratory methodological paper, we propose a combination of SA with Epistemic Network Analysis (ENA) as an alternative approach for providing richer qualitative and quantitative insights into Twitter discourse. We illustrate the application and potential use of these approaches by visualizing the differences between tweets directed or discussing Democrats and Republicans after the COVID-19 Stimulus Package announcement in the US. SA was integrated into ENA models in two ways: as a part of the blocking variable and as a set of codes. Our results suggest that incorporating SA into ENA allowed for a better understanding of how groups viewed the components of the stimulus issue by splitting them by sentiment and enabled a meaningful inclusion of data with singular subject focus into the ENA models.

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Author information

Authors and Affiliations

  1. Centre for the Science of Learning and Technology, University of Bergen, Bergen, Norway

    Kamila Misiejuk

  2. Department of Educational Psychology, University of Wisconsin, Madison, USA

    Jennifer Scianna, Karl Vachuska & David Williamson Shaffer

  3. Department of Education, University of Oslo, Oslo, Norway

    Rogers Kaliisa

Authors
  1. Kamila Misiejuk
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  2. Jennifer Scianna
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  3. Rogers Kaliisa
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  4. Karl Vachuska
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  5. David Williamson Shaffer
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Corresponding author

Correspondence to Kamila Misiejuk .

Editor information

Editors and Affiliations

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

    Andrew R. Ruis

  2. Pepperdine University, Malibu, CA, USA

    Seung B. Lee

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Misiejuk, K., Scianna, J., Kaliisa, R., Vachuska, K., Shaffer, D.W. (2021). Incorporating Sentiment Analysis with Epistemic Network Analysis to Enhance Discourse Analysis of Twitter Data. In: Ruis, A.R., Lee, S.B. (eds) Advances in Quantitative Ethnography. ICQE 2021. Communications in Computer and Information Science, vol 1312. Springer, Cham. https://doi.org/10.1007/978-3-030-67788-6_26

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  • DOI: https://doi.org/10.1007/978-3-030-67788-6_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-67787-9

  • Online ISBN: 978-3-030-67788-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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