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Group Decision and Negotiation

, Volume 26, Issue 5, pp 891–910 | Cite as

Toward the Automated Detection of Individuals’ Rationales in Large-Scale Online Open Participative Activities: A Conceptual Framework

  • Lu XiaoEmail author
  • Jennifer Stromer-Galley
  • Ágnes Sándor
Article

Abstract

In large-scale online open participative (LSOOP) activities, participants can join and leave at any time, and they often do not have a history of working together. Although the communication history is usually accessible to the participants in the environment, it is time consuming for them to process the communication data because of the large volume of messages. These characteristics make it difficult for one to keep track of, identify, and interpret the others’ ideas, opinions, and their rationales in LSOOP activities. We argue for a computational approach that automatically identifies and extracts the rationales from LSOOP communication data and presents them to the participants through rationale-based awareness tools. In this paper we bring together different and hitherto independent lines of research, and propose to use them in a conceptual framework integrating three analytical aspects related to the detection of rationales: linguistic, informational, and argumentative and communicative. We also review the design effort on offering rationale-based awareness in the LSOOP activities.

Keywords

Rationale detection Large-scale online open participative (LSOOP) activities Argumentation mining Awareness support 

Notes

Acknowledgements

This research is mainly supported by the Discovery Grant of Natural Sciences and Engineering Research Council of Canada (NSERC). The first author also thanks Xerox Research Center in Europe (XRCE) and Syracuse University for hosting her research leave during which the main ideas of this paper evolve.

References

  1. American Heritage\(\textregistered \) Dictionary. https://ahdictionary.com/word/search.html?q=argument
  2. Aharoni E, Polnarov A, Lavee T, Hershcovich D, Levy R, Rinott R, Gutfreund D, Slonim N (2014) A benchmark dataset for automatic detection of claims and evidence in the context of controversial topics. In: First workshop on argumentation mining at the 52nd annual meeting of the association for computational linguistics (ACL), vol 64. http://acl2014.org/acl2014/W14-21/W14-21-2014.pdf#page=76
  3. Bender EM, Morgan JT, Oxley M, Zachry M, Hutchinson B, Marin A, Zhang B, Ostendorf M (2011) Annotating social acts: authority claims and alignment moves in Wikipedia talk pages. In: Proceedings of the workshop on languages in social media. Association for Computational Linguistics, pp 48–57Google Scholar
  4. Biehl JT, Czerwinski M, Smith G, Robertson GG (2007) FASTDash: a visual dashboard for fostering awareness in software teams. In: Proceedings of the SIGCHI conference on human factors in computing systems (CHI ’07), April 28–May 3, San Jose, CA, USA, pp 1313–1322Google Scholar
  5. Biran O, Rambow O (2011) Identifying justifications in written dialogs. In: Proceeding of 2011 Fifth IEEE international conference on semantic computing (ICSC), pp 162–168Google Scholar
  6. Broadwell GA, Stromer-Galley J, Strzalkowski T, Shaikh S, Taylor S, Liu T, Boz U, Elia A, Jia L, Webb N (2012) Modeling sociocultural phenomena in discourse. J Nat Lang Eng 19:213–257CrossRefGoogle Scholar
  7. Bunt A, Lount M, Lauzon C (2012) Are explanations always important? a study of deployed, low-cost intelligent interactive systems. In: Proceedings of the 2012 ACM international conference on intelligent user interfaces. ACM, pp 169–178Google Scholar
  8. Carroll JM, Moran TP (1991) Introduction to this special issue on design rationale. Hum Comput Interact 6(3–4):197–200CrossRefGoogle Scholar
  9. Carroll JM, Rosson MB, Convertino G, Ganoe C (2006) Awareness and teamwork in computer-supported collaborations. Interact Comput 18:21–46CrossRefGoogle Scholar
  10. Carroll JM, Rosson MB, Farooq U, Xiao L (2009) Beyond being aware. Inf Organ 19(3):162–185CrossRefGoogle Scholar
  11. Carroll JM, Jiang H, Borge M (2015) Distributed collaborative homework activities in a problem-based usability engineering course. Educ Inf Technol 20(3):589–617CrossRefGoogle Scholar
  12. Convertino G, Hong LC, Nelson L, Pirolli P, Chi EH (2009) Activity aware-ness and social sensemaking 2.0: design of a task force workspace. In: Schmorrow DD, Estabrooke IV, Grootjen M (eds) Proceedings of the 5th international conference on foundations of augmented cognition. Neuroergonomics and operational neuroscience: held as part of HCI international 2009 (FAC ’09). Springer, Berlin, pp 128–137Google Scholar
  13. Farooq U, Carroll JM (2011) Supporting awareness in creative group work by exposing design rationale. Hum Technol Interdiscip J Hum ICT Environ 7(2):123–141Google Scholar
  14. Giboney JS, Brown SA, Lowry PB, Nunamaker JF (2015) User acceptance of knowledge-based system recommendations: explanations, arguments, and fit. Decis Support Syst 72:1–10CrossRefGoogle Scholar
  15. Gregor S, Benbasat I (1999) Explanations from intelligent systems: theoretical foundations and implications for practice. MIS Q 23(4):497–530Google Scholar
  16. Goudas T, Louizos C, Petasis G, Karkaletsis V (2014) Argument extraction from news, blogs, and social media. In: 8th hellenic conference on artificial intelligence (May 15–17, Ioannina, Greece). Springer, pp 287–299Google Scholar
  17. Green NL (2014) Towards creation of a corpus for argumentation mining the biomedical genetics research literature. In: First workshop on argumentation mining at the annual meeting of the association for computational linguistics, vol 11. https://www.aclweb.org/anthology/W/W14/W14-2102.pdf
  18. Hasan KS, Ng V (2013) Extra-linguistic constraints on stance recognition in ideological debates. In: ACL (2), pp 816–821Google Scholar
  19. Houngbo H, Mercer RE (2014) An automated method to build a corpus of rhetorically-classified sentences in biomedical texts. In: First workshop on argumentation mining at the annual meeting of the association for computational linguistics, vol 19. http://www.aclweb.org/anthology/W/W14/W14-21.pdf#page=31
  20. Iandoli L, Quinto I, Liddo AD, Shum SB (2014) Socially augmented argumentation tools: rationale, design and evaluation of a debate dashboard. Int J Hum Comput Stud 72(3):298–319CrossRefGoogle Scholar
  21. Ji YF, Eisenstein J (2014) Representation learning for text-level discourse parsing. In: Proceedings of the annual meeting of the association for computational linguistics, pp 13–24Google Scholar
  22. Khazaei K, Xiao L (2015a) Corpus-based analysis of rhetorical relations: a study of lexical cues. In: Proceedings of the IEEE international conference on semantic computing (ICSC), pp 417–423Google Scholar
  23. Khazaei K, Xiao L (2015b) Computational analysis of collective intelligence in conversational text. In: The 48th annual Hawaii international conference on system sciences (HICSS’48), Jan 5–8th, Kauai, HI, USA, pp 1596–1605Google Scholar
  24. Khazaei K, Xiao L, Mercer R (2015) A Graph-based method to disambiguate lexical cues for the classification of rhetorical relations. In: Workshop “computational semantics: linking lexical, sentential and discourse-level models”(LSDSem) at 2015 conference on empirical methods in natural language processing (EMNLP 2015), September 17–21, Lisbon, PortugalGoogle Scholar
  25. Kiesel J, Al-Khatib K, Hagen M, Stein BA (2015) A shared task on argumentation mining in newspaper editorials. In: 2nd workshop of argumentation mining at 2015 NAACL. http://www.aclweb.org/anthology/W15-0505
  26. Klein M (2012) Enabling large-scale deliberation using attention-mediation metrics. Comput Support Coop Work 21(4–5):449–473CrossRefGoogle Scholar
  27. Lamb A, Paul MJ, Dredze M (2013) Separating fact from fear: tracking flu infections on Twitter. In: HLT-NAACL, pp 789–795Google Scholar
  28. Lawrence J, Reed C (2015) Combining argument mining techniques. In: 2nd workshop of argumentation mining at 2015 NAACL. http://www.aclweb.org/anthology/W15-0516
  29. Lenman J (2010) Reasons for action: justification vs. explanation. In: Zalta EN (ed) The stanford encyclopedia of philosophy (Spring 2010 Edition). http://plato.stanford.edu/archives/spr2010/entries/reasons-just-vs-expl/
  30. Mann WC, Thompson SA (1988) Rhetorical structure theory: toward a functional theory of text organization. Text 8(3):243–281CrossRefGoogle Scholar
  31. Mao JY, Benbasat I (2000) The use of explanations in knowledge-based systems: cognitive perspectives and a process-tracing analysis. J Manag Inf Syst 17(2):153–179CrossRefGoogle Scholar
  32. Mao WT, Xiao L, Mercer R (2014a) Using text similarity and sentiment analysis to identify representative rationales in large-scale online deliberations. In: 5th workshop on computational approaches to subjectivity, sentiment & social media analysis at the 52nd annual meeting of the association for computational linguistics (ACL). Retrieved 8 Mar 2015. http://acl2014.org/acl2014/W14-26/pdf/W14-2624.pdf
  33. Mao WT, Mercer R, Xiao L (2014b) Extracting imperatives from wikipedia article for deletion discussions. In: First workshop on argumentation mining at the 52nd annual meeting of the association for computational linguistics (ACL). http://acl2014.org/acl2014/W14-21/pdf/W14-2117.pdf
  34. Mao WT, Mercer R, Xiao L (2015) Toward a knowledge repository for wikipedia article for deletion (AfD) discussions. Poster at the third international symposium of chinese CHI. ACM, New YorkGoogle Scholar
  35. Marin A, Zhang B, Ostendorf M (2011) Detecting forum authority claims in online discussions. In: Proceedings of the workshop on language in social media (LSM 2011). Association for Computational Linguistics, Portland, pp 39–47. http://www.aclweb.org/anthology/W11-0706
  36. Meyers RA, Brashers DE (1998) Argument in group decision making: explicating a process model and investigating the argument-outcome link. Commun Monogr 65:261–281CrossRefGoogle Scholar
  37. Meyers RA, Brashers DE, Hannder R (2000) Majority-minority influence: identifying argumentative patterns and predicting argument-outcome links. J Commun 50:3–30CrossRefGoogle Scholar
  38. Misra A, Anand P, Tree JEF, Walker MA (2015) Using summarization to discover argument facets in online idealogical dialog. In: NAACL HLT 2015, The 2015 conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, May 31–June 5, Denver, Colorado, USA, pp 430–440Google Scholar
  39. Mochales-Palau R, Moens MF (2009) Argumentation mining: the detection, classification and structure of arguments in text. In: Proceedings of the 12th international conference on artificial intelligence and law. ACM, pp 98–107Google Scholar
  40. Monk A (2003) Common ground in electronically mediated communication: Clark’s theory of language use. HCI models, theories, and frameworks: toward a multidisciplinary science, pp 265–289Google Scholar
  41. Moscovici S (1985) Social influence and conformity. In: Lindsey G, Aronson E (eds) Handbook of social psychology, vol 2, 3rd edn. Random House, New York, pp 347–412Google Scholar
  42. Mulkar-Mehta R, Welty C, Hobbs J, Hovy E (2011) Using part-of relations for discovering causality. In: Twenty-fourth international FLAIRS conference. http://www.aaai.org/ocs/index.php/FLAIRS/FLAIRS11/paper/view/2511/2991
  43. Noelle-Neuman E (1992) The spiral of silence: public opinion–our social skin, 2nd edn. University of Chicago Press, ChicagoGoogle Scholar
  44. Nguyen HV, Litman DJ (2015) Extracting argument and domain words for identifying argument components in texts. In: 2nd argumentation mining workshop at NAACL. http://www.aclweb.org/anthology/W15-0503
  45. Oraby S, Reed L, Compton R, Riloff E, Walker M, Whittaker S (2015) And that’s a fact: distinguishing factual and emotional argumentation in online dialogue. In: 2nd argumentation mining workshop at NAACL. http://www.aclweb.org/anthology/W15-0515
  46. Park J, Cardie C (2014) Identifying appropriate support for propositions in online user comments. In: Proceedings of the annual meeting on association for computational linguistics, vol 29. http://aclweb.org/anthology/W/W14/W14-2105.pdf
  47. Park J, Katiyar A, Yang B (2015) Conditional random fields for identifying appropriate types of support for propositions in online user comments. In: 2nd workshop of argumentation mining at 2015 NAACL. http://www.cs.cornell.edu/~jpark/papers/jpark_naaclw15.pdf
  48. Peldszus A, Stede M (2013) From argument diagrams to argumentation mining in texts: a survey. Int J Cognit Inf Nat Intell (IJCINI) 7(1):1–31CrossRefGoogle Scholar
  49. Pendar N, Cotos E (2008) Automatic identification of discourse moves in scientific article introductions. In: Proceedings of the third workshop on innovative use of NLP for building educational applications. Association for Computational Linguistics, pp 62–70Google Scholar
  50. Reed C, Mochales-Palau R, Rowe G, Moens MF (2008) Language resources for studying argument. In: Proceedings of the 6th conference on language resources and evaluation-LREC 2008, pp 91–100Google Scholar
  51. Reisert P, Inoue N, Okazaki N, Inui K (2015) A computational approach for generating Toulmin model argumentation. In: The 2nd argumentation mining workshop at the conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT), May 31–June 5, Denver, CO, USA. http://www.aclweb.org/anthology/W15-0507
  52. Rafaeli S (1988) Interactivity: From new media to communication. In: Hawkins RP, Wiemann JM, Pingree S (eds) Advancing communication science: merging mass and interpersonal processes. Sage, Newbury Park, pp 110–134Google Scholar
  53. Ridgeway C (1982) Status in groups: the importance of motivation. Am Sociol Rev 47:76–88CrossRefGoogle Scholar
  54. Rogers B, Qiao YC, Gung J, Mathur T, Burge JE (2014) Using text mining techniques to extract rationale from existing documentation. In: Gero JS, Hanna S (eds) Design computing and cognition ’14, pp 457–474. doi: 10.1007/978-3-319-14956-1_26
  55. Rosenthal S, McKeown K (2012) Detecting opinionated claims in online discussions. In: 2012 IEEE sixth international conference on semantic computing, pp 30–37Google Scholar
  56. Sándor Á (2007) Modeling metadiscourse conveying the author’s rhetorical strategy in biomedical research abstracts. Revue Française de Linguistique Appliquée 12(2):97–108Google Scholar
  57. Schneider K (2006) Rationale as a by-product. In: Dutoit AH, McCall R, Mistrik I, Paech B (eds) Rationale management in software engineering. Springer, Berlin, pp 91–109Google Scholar
  58. Schneider J (2014) Automated argumentation mining to the rescue? Envisioning argumentation and decision-making support for debates in open online collaboration communities. In: First workshop on argumentation mining at the 52nd annual meeting of the association for computational linguistics (ACL). http://jodischneider.com/pubs/aclargmining2014.pdf
  59. Sobhani P, Inkpen D, Matwin S (2015) From argumentation mining to stance classification. In: 2nd workshop of argumentation mining at 2015 NAACL. http://www.aclweb.org/anthology/W15-0509
  60. Stromer-Galley J, Bryant L, Bimber B (2015) Context and medium matter: expressing disagreements online and face-to-face in political deliberation. J Public Delib 11:1. http://www.publicdeliberation.net/jpd/vol11/iss1/art1/
  61. Swales J (1990) English in academic and research settings. Cambridge University Press, CambridgeGoogle Scholar
  62. Taboada M (2006) Discourse markers as signals (or not) of rhetorical relations. J Pragmat 38(4):567–592CrossRefGoogle Scholar
  63. Teufel S (1998) Meta-discourse markers and problem-structuring in scientific articles. In: Proceedings of the workshop on discourse relations and discourse markers at the 17th international conference on computational linguistics, pp 43–49Google Scholar
  64. Teufel S, Moens M (2002) Summarizing scientific articles: experiments with relevance and rhetorical status. Comput linguist 28(4):409–445Google Scholar
  65. Toulmin SE (1958) The uses of argument. Cambridge University Press, CambridgeGoogle Scholar
  66. Van Eemeren FH, Grootendorst R, Johnson RH, Plantin C, Willard CA (2013) Fundamentals of argumentation theory: a handbook of historical backgrounds and contemporary developments. Routledge, AbingdonGoogle Scholar
  67. Wacholder N, Muresan S, Ghosh D, Aakhus M (2014) Annotating multiparty discourse: challenges for agreement metrics. In: Proceedings of the 8th linguistic annotation workshop, August 24–25, Dublin, Ireland, pp 120–128Google Scholar
  68. Walker MA, Anand P, Abbott R, Grant R (2012) Stance classification using dialogic properties of persuasion. In: Proceedings of the 2012 conference of the North American chapter of the association for computational linguistics: human language technologies. Association for Computational Linguistics, pp 592–596Google Scholar
  69. Walton D, Reed C, Macagno F (2008) Argumentation schemes, 1st edn. Cambridge University Press, CambridgeGoogle Scholar
  70. Wyner A, Schneider J, Atkinson K, Bench-Capon TJ (2012) Semi-automated argumentative analysis of online product reviews. In: Fourth international conference on computational models of argument, Sept 10–12, Vienna, Austria, vol 245, pp 43–50Google Scholar
  71. Xiao L (2013) The effects of a shared free form rationale space in collaborative learning activities. J Syst Softw 86(7):1727–1737CrossRefGoogle Scholar
  72. Xiao L (2014) Effects of rationale awareness in online ideation crowdsourcing tasks. J Am Soc Inf Sci Technol 65:1707–1720. doi: 10.1002/asi.23079 CrossRefGoogle Scholar
  73. Xiao L, Mazalov V (2012) Message Visualizer: A visualization tool for chat messages. In: Proceedings of the 2012 iConference, Feb 7–10, Toronto, Canada, pp 426–428Google Scholar
  74. Xiao L, Carroll JM (2013) The effects of rationale awareness on individual reflection: processes in virtual group activities. Int J e-Collab 9(2):78–95Google Scholar
  75. Xiao L, Askin N (2014) What influences online deliberation? Wikipedia study. J Am Soc Inf Sci Technol 65:898–910CrossRefGoogle Scholar
  76. Xiao L, Khazaei T (2014) ProjectTales: reusing changes and change rationales in project management. In: Proceedings of iConference 2014. https://www.ideals.illinois.edu/handle/2142/47344
  77. Xiao L, Askin N (2015) Rationale sharing in large-scale online deliberations. In: 2015 Proceeding of iConference. http://hdl.handle.net/2142/73741
  78. Xiao L, Carroll JM (2015) Shared practices in articulating and sharing rationale: an empirical study. Int J e-Collab 11(4):11–39Google Scholar
  79. Ye LR, Johnson PE (1995) The impact of explanation facilities on user acceptance of expert systems advice. MIS Q 19(2):157–172CrossRefGoogle Scholar

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© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.School of Information StudiesSyracuse UniversitySyracuseUSA
  2. 2.Parsing and Semantics Research GroupXerox Research Centre EuropeMeylanFrance

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