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International Symposium on Benchmarking, Measuring and Optimization

Bench 2019: Benchmarking, Measuring, and Optimizing pp 204–214Cite as

Causal Learning in Question Quality Improvement

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12093))

Abstract

To improve the quality of questions asked in Community-based questions answering forums, we create a new dataset from the website, Stack Overflow, which contains three components: (1) context: the text features of questions, (2) treatment: categories of revision suggestions and (3) outcome: the measure of question quality (e.g., the number of questions, upvotes or clicks). This dataset helps researchers develop causal inference models towards solving two problems: (i) estimating the causal effects of aforementioned treatments on the outcome and (ii) finding the optimal treatment for the questions. Empirically, we performed experiments with three state-of-the-art causal effect estimation methods on the contributed dataset. In particular, we evaluated the optimal treatments recommended by the these approaches by comparing them with the ground truth labels – treatments (suggestions) provided by experts.

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Notes

  1. 1.

    https://stackoverflow.com/.

  2. 2.

    https://www.quora.com/.

  3. 3.

    https://www.zhihu.com.

  4. 4.

    https://stackexchange.com/sites?view=list#questionsperday.

  5. 5.

    https://meta.stackexchange.com/questions/180692/why-do-i-receive-downvotes-when-i-am-genuinely-trying-to-learn/.

  6. 6.

    https://stackoverflow.com/help/how-to-ask.

  7. 7.

    https://stackoverflow.com/help/how-to-ask.

  8. 8.

    https://archive.org/details/stackexchange.

  9. 9.

    https://stackexchange.com/.

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Acknowledgement

This material is based upon work supported by ARO/ARL and the National Science Foundation (NSF) Grant #1610282, NSF #1909555.

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Authors and Affiliations

  1. Arizona State University, Tempe, AZ, 85281, USA

    Yichuan Li, Ruocheng Guo, Weiying Wang & Huan Liu

Authors
  1. Yichuan Li
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  2. Ruocheng Guo
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  3. Weiying Wang
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  4. Huan Liu
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Corresponding author

Correspondence to Yichuan Li .

Editor information

Editors and Affiliations

  1. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Wanling Gao

  2. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Jianfeng Zhan

  3. School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA

    Geoffrey Fox

  4. Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA

    Xiaoyi Lu

  5. Texas Advanced Computing Center, The University of Texas at Austin, Austin, TX, USA

    Dan Stanzione

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Li, Y., Guo, R., Wang, W., Liu, H. (2020). Causal Learning in Question Quality Improvement. In: Gao, W., Zhan, J., Fox, G., Lu, X., Stanzione, D. (eds) Benchmarking, Measuring, and Optimizing. Bench 2019. Lecture Notes in Computer Science(), vol 12093. Springer, Cham. https://doi.org/10.1007/978-3-030-49556-5_20

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  • DOI: https://doi.org/10.1007/978-3-030-49556-5_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49555-8

  • Online ISBN: 978-3-030-49556-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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