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

1. Allamanis, M., Sutton, C.: Why, when, and what: analyzing stack overflow questions by topic, type, and code. In: 2013 10th Working Conference on Mining Software Repositories (MSR), pp. 53–56. IEEE (2013)

   Google Scholar 

2. Anderson, A., Huttenlocher, D., Kleinberg, J., Leskovec, J.: Discovering value from community activity on focused question answering sites: a case study of stack overflow. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 850–858 (2012)

   Google Scholar 

3. Barua, A., Thomas, S.W., Hassan, A.E.: What are developers talking about? An analysis of topics and trends in stack overflow. Empir. Softw. Eng. 19(3), 619–654 (2014)

   Article  Google Scholar 

4. Bazelli, B., Hindle, A., Stroulia, E.: On the personality traits of stackOverflow users. In: 2013 IEEE International Conference on Software Maintenance, pp. 460– 463. IEEE (2013)

   Google Scholar 

5. Brooke, S.: Trouble in programmer’s paradise: gender-biases in sharing and recognising technical knowledge on stack overflow. Inf. Commun. Soc. 24(14), 2091–2112 (2021)

   Article  Google Scholar 

6. Calefato, F., Lanubile, F., Marasciulo, M.C., Novielli, N.: Mining successful answers in stack overflow. In: 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories, pp. 430–433. IEEE (2015)

   Google Scholar 

7. Calefato, F., Lanubile, F., Novielli, N.: How to ask for technical help? Evidence based guidelines for writing questions on stack overflow. Inf. Softw. Technol. 94, 186–207 (2018)

   Article  Google Scholar 

8. Correa, D., Sureka, A.: Fit or unfit: analysis and prediction of ‘closed questions’ on stack overflow. In: Proceedings of the First ACM Conference on Online Social Networks, pp. 201–212 (2013)

   Google Scholar 

9. Ford, D., Harkins, A., Parnin, C.: Someone like me: how does peer parity influence participation of women on stack overflow? In: 2017 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), pp. 239–243. IEEE (2017)

   Google Scholar 

10. Ford, D., Smith, J., Guo, P.J., Parnin, C.: Paradise unplugged: Identifying barriers for female participation on stack overflow. In: Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering, pp. 846–857 (2016)

    Google Scholar 

11. Gee, J.P.: Semiotic social spaces and affinity spaces. In: Beyond Communities of Practice Language Power and Social Context, p. 214232 (2005)

    Google Scholar 

12. Gee, J.P.: Situated Language and Learning: A Critique of Traditional Schooling. Routledge (2012)

    Google Scholar 

13. Gee, J.P., Hayes, E.: Nurturing affinity spaces and game-based learning. In: Games, Learning, and Society: Learning and Meaning in the Digital Age, vol. 123, pp. 1–40 (2012)

    Google Scholar 

14. Hart, K., Sarma, A.: Perceptions of answer quality in an online technical question and answer forum. In: Proceedings of the 7th International Workshop on Cooperative and Human Aspects of Software Engineering, pp. 103–106 (2014)

    Google Scholar 

15. Moutidis, I., Williams, H.T.: Community evolution on stack overflow. PLoS ONE 16(6), e0253010 (2021)

    Article  Google Scholar 

16. Nasehi, S.M., Sillito, J., Maurer, F., Burns, C.: What makes a good code example?: A study of programming Q&A in stackoverflow. In: 2012 28th IEEE International Conference on Software Maintenance (ICSM), pp. 25–34. IEEE (2012)

    Google Scholar 

17. Novielli, N., Calefato, F., Lanubile, F.: Towards discovering the role of emotions in stack overflow. In: Proceedings of the 6th International Workshop on Social Software Engineering, pp. 33–36 (2014)

    Google Scholar 

18. Saldaña, J.: The Coding Manual for Qualitative Researchers. Sage (2021)

    Google Scholar 

19. Shaffer, D.W.: Models of situated action: computer games and the problem of transfer. In: Games Learning, And Society: Learning and Meaning in the Digital Age, pp. 403–431 (2012)

    Google Scholar 

20. Shaffer, D.W., Collier, W., Ruis, A.R.: A tutorial on epistemic network analysis: analyzing the structure of connections in cognitive, social, and interaction data. J. Learn. Anal. 3(3), 9–45 (2016)

    Article  Google Scholar 

21. Siebert-Evenstone, A.L., Irgens, G.A., Collier, W., Swiecki, Z., Ruis, A.R., Shaffer, D.W.: In search of conversational grain size: modeling semantic structure using moving stanza windows. J. Learn. Anal. 4(3), 123–139 (2017)

    Google Scholar 

22. Stephany, F., Braesemann, F., Graham, M.: Coding together–coding alone: the role of trust in collaborative programming. Inf. Commun. Soc. 24(13), 1944–1961 (2021)

    Article  Google Scholar 

23. Treude, C., Robillard, M.P.: Understanding stack overflow code fragments. In: 2017 IEEE International Conference on Software Maintenance and Evolution (ICSME), pp. 509–513. IEEE (2017)

    Google Scholar 

24. Wang, S., Lo, D., Jiang, L.: An empirical study on developer interactions in stackoverflow. In: Proceedings of the 28th Annual ACM Symposium on Applied Computing, pp. 1019–1024 (2013)

    Google Scholar 

25. Zörgő, S., Jeney, A., Csajbók-Veres, K., Mkhitaryan, S., Susánszky, A.: Mapping the content structure of online diabetes support group activity on Facebook. In: Wasson, B., Zörgő, S. (eds.) International Conference on Quantitative Ethnography, pp. 221–236. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-93859-8_15

Download references