From Arguments and Reviewers to their Simulation - Reproducing a Case-Study

Simone Gabbriellini, Francesco Santini


We propose an exploratory study on arguments in reviews. Firstly, we extract positive (in favour of purchase) and negative (against it) arguments from each review concerning a selected product. We accomplish this information extraction manually, scanning all the related reviews. Secondly, we link extracted arguments to the rating score, to the length, and to the date of reviews, in order to undertand how they are connected. As a result, we show that negative arguments are quite sparse in the beginning of such social review-process, while positive arguments are more equally distributed along the timeline. As a final step, we replicate the behaviour of reviewers as agents, by simulating how they assemble reviews in the form of arguments. In such a way, we show we are able to mirror the measured experiment through a simulation that takes into account both positive and negative arguments.


  1. Anderson, E. W. (1998). Customer satisfaction and word of mouth. Journal of Service Research, 1(1):517.
  2. Balázs, K. (2014). The duality of organizations and audiences, pages 397-418. John Wiley & Sons, Ltd.
  3. Baldassarri, D. and Bearman, P. (2007). Dynamics of political polarization. American Sociological Review, 72:784811.
  4. Bistarelli, S. and Santini, F. (2010). A common computational framework for semiring-based argumentation systems. In ECAI 2010 - 19th European Conference on Artificial Intelligence, volume 215 of FAIA, pages 131-136. IOS Press.
  5. Bistarelli, S. and Santini, F. (2013). Coalitions of arguments: An approach with constraint programming. Fundam. Inform., 124(4):383-401.
  6. Chatterjee, P. (2001). Online reviews do consumers use them? In Gilly, M. C. and Myers-Levy, J., editors, ACR 2001 Proceedings, pages 129-134. Association for Consumer Research.
  7. Chevalier, J. and Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of Marketing, 43(3):345354.
  8. Clauset, A., Shalizi, C., and Newman, M. (2009). Powerlaw distributions in empirical data. SIAM Review, 51(4):661-703.
  9. Dellarocas, C. (2003). The digitization of word of mouth: promise and challenges of online feedback mechanisms. Management Science, 49(10):14071424.
  10. Flache, A. and Macy, M. W. (2011). Local convergence and global diversity: From interpersonal to social influence. Journal of Conflict Resolution , 55(6):970-995.
  11. Gabbriellini, S. (2014). The evolution of online forums as communication networks: An agent-based model. Revue Francaise de Sociologie, 4(55):805-826.
  12. Gabbriellini, S. and Santini, F. (2015). A micro study on the evolution of arguments in's reviews. In PRIMA 2015: Principles and Practice of MultiAgent Systems - 18th International Conference, volume 9387, pages 284-300. Springer.
  13. Gillespie, C. (2015). Fitting heavy tailed distributions: the powerlaw package. Journal of Statistical Software, 64(2).
  14. Goldenberg, J., Libai, B., and Muller, E. (2001). Talk of the network: a complex systems look at the underlying process of word-of-mouth. Marketing Letters, 12(3):211223.
  15. Hedstrom, P. (2005). Dissectin the Social: on the Principles of Analytical Sociology. Cambridge University Press, 1st edition.
  16. Hu, M. and Liu, B. (2004). Mining and summarizing customer reviews. In Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 7804, pages 168-177. ACM.
  17. Lippi, M. and Torroni, P. (2015). Context-independent claim detection for argument mining. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI 2015, pages 185-191. AAAI Press.
  18. Macy, M. W. and Skvoretz, J. (1998). The evolution of trust and cooperation between strangers: A computational model. American Sociological Review, 63(5):638- 660.
  19. Macy, M. W. and Willer, R. (2002). From factors to actors: Computational sociology and agent-based modeling. Annual Review of Sociology, 28:143-166.
  20. Manzo, G. (2007). Variables, mechanisms, and simulations : Can the three methods be synthesized ? Revue franaise de sociologie, 48:156.
  21. Manzo, G. (2013). Educational choices and social interactions: A formal model and a computational test. Comparative Social Research, 30:47-100.
  22. Mercier, H. and Sperger, D. (2011). Why do humans reason? Arguments for an argumentative theory. Behavioral and Brain Sciences, 34(2):57-74.
  23. Moe, W. W. and Schweidel, D. A. (2012). Online product opinions: Incidence, evaluation, and evolution. Marketing Science, 31(3):372386.
  24. Moody, J. (2008). Network Dynamics, pages 447-474. Peter Hedstrom and Peter S. Bearman.
  25. Nagle, F. and Riedl, C. (2014). Online word of mouth and product quality disagreement. In ACAD MANAGE PROC, Meeting Abstract Supplement. Academy of Management.
  26. Rogers, E. (2003). Diffusion of Innovations. Simone & Schuster, 5st edition.
  27. Squazzoni, F. (2012). Agent-Based Computational Sociology. Wiley, 1st edition.
  28. Stokes, D. and Lomax, W. (2002). Taking control of word of mouth marketing: the case of an entrepreneurial hotelier. Journal of Small Business and Enterprise Development, 9(4):349357.
  29. Villalba, M. P. G. and Saint-Dizier, P. (2012). A framework to extract arguments in opinion texts. IJCINI, 6(3):62- 87.
  30. Wang, B.-C., Zhu, W.-Y., and Chen, L.-J. (2008). Improving the amazon review system by exploiting the credibility and time-decay of public reviews. In Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03, WI-IAT 7808, pages 123-126. IEEE Computer Society.
  31. Wyner, A., Schneider, J., Atkinson, K., and Bench-Capon, T. J. M. (2012). Semi-automated argumentative analysis of online product reviews. In Computational Models of Argument - Proceedings of COMMA 2012, volume 245 of FAIA, pages 43-50. IOS Press.
  32. Zhu, F. and Zhang, X. (2006). The influence of online consumer reviews on the demand for experience goods: The case of video games. In Proceedings of the International Conference on Information Systems, ICIS, page 25. Association for Information Systems.

Paper Citation

in Harvard Style

Gabbriellini S. and Santini F. (2016). From Arguments and Reviewers to their Simulation - Reproducing a Case-Study . In Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-172-4, pages 74-83. DOI: 10.5220/0005816200740083

in Bibtex Style

author={Simone Gabbriellini and Francesco Santini},
title={From Arguments and Reviewers to their Simulation - Reproducing a Case-Study},
booktitle={Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},

in EndNote Style

JO - Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - From Arguments and Reviewers to their Simulation - Reproducing a Case-Study
SN - 978-989-758-172-4
AU - Gabbriellini S.
AU - Santini F.
PY - 2016
SP - 74
EP - 83
DO - 10.5220/0005816200740083