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What Makes a Good Answer? Analyzing the Content Structure of Answers to Stack Overflow’s Most Popular Question

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Advances in Quantitative Ethnography (ICQE 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1785))

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Abstract

Stack Overflow provides a popular and practical community for software developers to ask and answer questions related to coding. These answers are ranked by users to evaluate their quality. For newcomers, participating in answering questions can be challenging, as they must learn what the expectations for answers in this online community are. In this paper, using epistemic networks, we analyze the content structure of the answers posted to Stack Overflow’s most highly ranked question with the goal of understanding characteristics of answers valued by the Stack Overflow community. Network models show that answer content is qualitatively different between high and low ranked answers, with high ranked answers including general explanations and code examples to contextualize question-specific code and explanations. We discuss how these findings could be used to better support and scaffold new participants in crafting their answers.

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Acknowledgements

Special thanks to Nidhi Nasiar for support with data coding.

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Authors and Affiliations

  1. University of Pennsylvania, Philadelphia, PA, 19104, USA

    Luis Morales-Navarro

  2. Drexel University, Philadelphia, PA, 19104, USA

    Amanda Barany

Authors
  1. Luis Morales-Navarro
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  2. Amanda Barany
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Corresponding authors

Correspondence to Luis Morales-Navarro or Amanda Barany .

Editor information

Editors and Affiliations

  1. University of Oslo, Oslo, Norway

    Crina Damşa

  2. Drexel University School of Education, Philadelphia, PA, USA

    Amanda Barany

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Morales-Navarro, L., Barany, A. (2023). What Makes a Good Answer? Analyzing the Content Structure of Answers to Stack Overflow’s Most Popular Question. In: Damşa, C., Barany, A. (eds) Advances in Quantitative Ethnography. ICQE 2022. Communications in Computer and Information Science, vol 1785. Springer, Cham. https://doi.org/10.1007/978-3-031-31726-2_26

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  • DOI: https://doi.org/10.1007/978-3-031-31726-2_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-31725-5

  • Online ISBN: 978-3-031-31726-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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