Analysis of Online Discussions in Support of Requirements Discovery

  • Itzel Morales-RamirezEmail author
  • Fitsum Meshesha Kifetew
  • Anna Perini
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10253)


Feedback about software applications and services that end-users express through web-based communication platforms represents an invaluable knowledge source for diverse software engineering tasks, including requirements elicitation. Research work on automated analysis of textual messages in app store reviews, open source software (OSS) mailing-lists and user forums has been rapidly increasing in the last five years. NLP techniques are applied to filter out irrelevant data, text mining and automated classification techniques are then used to classify messages into different categories, such as bug report and feature request. Our research focuses on online discussions that take place in user forums and OSS mailing-lists, and aims at providing automated analysis techniques to discover contained requirements. In this paper, we present a speech-acts based analysis technique, and experimentally evaluate it on a dataset taken from a widely used OSS project.


Requirements engineering Linguistic analysis Sentiment analysis Automated classification techniques Speech-acts 



We thank Rob Weir for providing the OpenOffice dataset. This work is a result of the SUPERSEDE project, funded by the H2020 EU Framework Programme under agreement number 644018. The first author is partially funded by INFOTEC under the project “081-022-00-FORTALECIMIENTO E INVERSIÓN”.


  1. 1.
    Adam, S., Seyff, N., Perini, A., Metzger, A.: Message from the chairs. In: 2015 IEEE 1st International Workshop on Crowd-Based Requirements Engineering (CrowdRE), pp. iii–iv, August 2015. doi: 10.1109/CrowdRE.2015.7367580
  2. 2.
    Arnaoudova, V., Haiduc, S., Marcus, A., Antoniol, G.: The use of text retrieval and natural language processing in software engineering. In: Proceedings of the 37th, ICSE 2015, pp. 949–950. IEEE Press (2015)Google Scholar
  3. 3.
    Caleb, C., Schrock, D., Dauterman, P.: Speech act analysis within social network sites’ status messages. In: 59th International Communication Association Conference, vol. 20, May 2009Google Scholar
  4. 4.
    Carreño, L.V.G., Winbladh, K.: Analysis of user comments: an approach for software requirements evolution. In: Notkin, D., Cheng, B.H.C., Pohl, K. (eds.) ICSE, pp. 582–591. IEEE/ACM (2013)Google Scholar
  5. 5.
    Cowie, J., Lehnert, W.: Information extraction. Commun. ACM 39(1), 80–91 (1996)CrossRefGoogle Scholar
  6. 6.
    Cunningham, H., Maynard, D., Bontcheva, K., Tablan, V., Aswani, N., Roberts, I., Gorrell, G., Funk, A., Roberts, A., Damljanovic, D., Heitz, T., Greenwood, M.A., Saggion, H., Petrak, J., Li, Y., Peters, W.: Text Processing with GATE (Version 6) (2011). ISBN: 978-0956599315.
  7. 7.
    Di Sorbo, A., Panichella, S., Alexandru, C.V., Shimagaki, J., Visaggio, C.A., Canfora, G., Gall, H.C.: What would users change in my app? summarizing app reviews for recommending software changes. In: Proceedings of the 2016 24th ACM SIGSOFT International Symposium FSE, pp. 499–510. ACM (2016)Google Scholar
  8. 8.
    Fang, X., Zhan, J.: Sentiment analysis using product review data. J. Big Data 2(1), 1–14 (2015)CrossRefGoogle Scholar
  9. 9.
    Feng, D., Shaw, E., Kim, J., Hovy, E.H.: An intelligent discussion-bot for answering student queries in threaded discussions. In: International Conference on Intelligent User Interfaces, pp. 171–177. ACM (2006)Google Scholar
  10. 10.
    Godfrey, J.J., Holliman, E.C., McDaniel, J.: SWITCHBOARD: telephone speech corpus for research and development. In: Acoustics, Speech, and Signal Processing, ICASSP-1992, vol. 1, pp. 517–520 (1992)Google Scholar
  11. 11.
    Guzman, E., Alkadhij, R., Seyff, N.: A needle in a haystack: what do Twitter users say about software? In: IEEE 24th International Conference in Requirements Engineering, pp. 96–105 (2016)Google Scholar
  12. 12.
    Guzman, E., Aly, O., Bruegge, B.: Retrieving diverse opinions from app reviews. In: 2015 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), pp. 1–10, October 2015Google Scholar
  13. 13.
    Keertipati, S., Savarimuthu, B.T.R., Licorish, S.A.: Approaches for prioritizing feature improvements extracted from app reviews. In: Proceedings of the 20th International Conference EASE, pp. 33:1–33:6. ACM, New York (2016)Google Scholar
  14. 14.
    Kim, J., Chern, G., Feng, D., Shaw, E., Hovy, E.: Mining and assessing discussions on the web through speech act analysis. In: Proceedings of the Workshop on Web Content Mining with Human Language Technologies (2006)Google Scholar
  15. 15.
    Maalej, W., Nabil, H.: Bug report, feature request, or simply praise? On automatically classifying app reviews. In: 2015 IEEE 23rd International Requirements Engineering Conference (RE), pp. 116–125. IEEE (2015)Google Scholar
  16. 16.
    Manning, C.D., Surdeanu, M., Bauer, J., Finkel, J., Bethard, S.J., McClosky, D.: The Stanford CoreNLP natural language processing toolkit. In: Association for Computational Linguistics (ACL) System Demonstrations, pp. 55–60 (2014)Google Scholar
  17. 17.
    Martin, W., Sarro, F., Jia, Y., Zhang, Y., Harman, M.: A survey of app store analysis for software engineering. IEEE Trans. Softw. Eng., 1, 5555 (2016). doi: 10.1109/TSE.2016.2630689
  18. 18.
    Morales-Ramirez, I., Perini, A.: Discovering speech acts in online discussions: a tool-supported method. In: Joint Proceedings of the CAiSE 2014 Forum, volume 1164 of CEUR Workshop Proceedings, pp. 137–144. (2014)Google Scholar
  19. 19.
    Morales-Ramirez, I., Perini, A., Ceccato, M.: Towards supporting the analysis of online discussions in OSS communities: a speech-act based approach. In: Nurcan, S., Pimenidis, E. (eds.) CAiSE Forum 2014. LNBIP, vol. 204, pp. 215–232. Springer, Cham (2015). doi: 10.1007/978-3-319-19270-3_14 CrossRefGoogle Scholar
  20. 20.
    Morales-Ramirez, I., Perini, A., Guizzardi, R.S.S.: An ontology of online user feedback in software engineering. Appl. Ontol. 10(3–4), 297–330 (2015)CrossRefGoogle Scholar
  21. 21.
    Neulinger, K., Hannemann, A., Klamma, R., Jarke, M.: A longitudinal study of community-oriented open source software development. In: Nurcan, S., Soffer, P., Bajec, M., Eder, J. (eds.) CAiSE 2016. LNCS, vol. 9694, pp. 509–523. Springer, Cham (2016). doi: 10.1007/978-3-319-39696-5_31 Google Scholar
  22. 22.
    Novielli, N., Strapparava, C.: Dialogue act classification exploiting lexical semantics. In: Conversational Agents and Natural Language Interaction: Techniques and Effective Practices, pp. 80–106. IGI Global (2011)Google Scholar
  23. 23.
    Panichella, S., Di Sorbo, A., Guzman, E., Visaggio, C.A., Canfora, G., Gall, H.C.: How can i improve my app? Classifying user reviews for software maintenance and evolution. In: IEEE International Conference on Software Maintenance and Evolution (ICSME), pp. 281–290. IEEE (2015)Google Scholar
  24. 24.
    Searle, J.R.: Speech Acts: An Essay in the Philosophy of Language, vol. 626. Cambridge University Press, Cambridge (1969)CrossRefGoogle Scholar
  25. 25.
    Stolcke, A., Coccaro, N., Bates, R., Taylor, P., Van Ess-Dykema, C., Ries, K., Shriberg, E., Jurafsky, D., Martin, R., Meteer, M.: Dialogue act modeling for automatic tagging and recognition of conversational speech. Comput. Linguist. 26(3), 339–373 (2000)CrossRefGoogle Scholar
  26. 26.
    Villarroel, L., Bavota, G., Russo, B., Oliveto, R., Penta, M.D.: Release planning of mobile apps based on user reviews. In: Proceedings of the 38th International Conference on Software Engineering, pp. 14–24. ACM (2016)Google Scholar
  27. 27.
    Wohlin, C., Runeson, P., Höst, M., Ohlsson, M.C., Regnell, B., Wesslén, A.: Experimentation in Software Engineering: An Introduction. Kluwer Academic Publishers, Norwell (2000)CrossRefzbMATHGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Itzel Morales-Ramirez
    • 1
    Email author
  • Fitsum Meshesha Kifetew
    • 2
  • Anna Perini
    • 2
  1. 1.INFOTECTlalpan, Mexico CityMexico
  2. 2.Software Engineering Research UnitFondazione Bruno KesslerTrentoItaly

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