International Journal of Fuzzy Systems

, Volume 21, Issue 3, pp 963–977 | Cite as

A Linguistic Intuitionistic Cloud Decision Support Model with Sentiment Analysis for Product Selection in E-commerce

  • Ruxia Liang
  • Jian-qiang WangEmail author


Online product reviews significantly impact the online purchase decisions of consumers. However, extant decision support models have neglected the randomness and fuzziness of online reviews and the interrelationships among product features. This study presents an integrated decision support model that can help customers discover desirable products online. This proposed model encompasses three modules: information acquisition, information transformation, and integration model. We use the information acquisition module to gather linguistic intuitionistic fuzzy information in each review through sentiment analysis. We also apply the information transformation module to convert the linguistic intuitionistic fuzzy information into linguistic intuitionistic normal clouds (LINCs). The integration module is employed to obtain the overall LINCs for each product. A ranked list of alternative products is determined. A case study on is then provided to illustrate the effectiveness and feasibility of the proposal, along with sensitivity and comparison analyses, to verify its stability and superiority. Finally, conclusions and future research directions are suggested.


Decision support model Online reviews Sentiment analysis Linguistic intuitionistic fuzzy sets 



The authors would like to thank the editors and anonymous reviewers for their great help on this study. This work was supported by the Fundamental Research Funds for the Central Universities of Central South University (No. 502211710).

Compliance with Ethical Standards

Conflict of interest

The authors declare that there is no conflict of interest regarding the publication of this paper.


  1. 1.
    Liu, K., Luo, X., Zhang, L.: Evaluation of China’s B2C e-commerce website: an analysis of factors that influence online buying decision. Int. J. Multimed. Ubiquitous Eng. 11(3), 143–156 (2016)Google Scholar
  2. 2.
    Chen, X., Xue, Y., Zhao, H.Y., Lu, X., Hu, X.H., Ma, Z.H.: A novel feature extraction methodology for sentiment analysis of product reviews. Neural Comput. Appl. (2018). Google Scholar
  3. 3.
    Büschken, J., Allenby, G.M.: Sentence-based text analysis for customer reviews. Market. Sci. 35(6), 953–975 (2016)Google Scholar
  4. 4.
    Zhou, F., Jiao, J.R., Yang, X.J., Lei, B.: Augmenting feature model through customer preference mining by hybrid sentiment analysis. Expert Syst. Appl. 89, 306–317 (2017)Google Scholar
  5. 5.
    Gao, B., Hu, N., Bose, I.: Follow the herd or be myself? An analysis of consistency in behavior of reviewers and helpfulness of their reviews. Decis. Support Syst. 95, 1–11 (2017)Google Scholar
  6. 6.
    Gavilan, D., Avello, M., Martinez-Navarro, G.: The influence of online ratings and reviews on hotel booking consideration. Tour. Manag. 66, 53–61 (2018)Google Scholar
  7. 7.
    Chen, A., Lu, Y., Wang, B.: Customers’ purchase decision-making process in social commerce: a social learning perspective. Int. J. Inf. Manag. 37(6), 627–638 (2017)Google Scholar
  8. 8.
    Maslowska, E., Malthouse, E.C., Viswanathan, V.: Do customer reviews drive purchase decisions? The moderating roles of review exposure and price. Decis. Support Syst. 98, 1–9 (2017)Google Scholar
  9. 9.
    Wang, W., Tan, G., Wang, H.: Cross-domain comparison of algorithm performance in extracting aspect-based opinions from Chinese online reviews. Int. J. Mach. Learn. Cybernet. 8(3), 1053–1070 (2016)Google Scholar
  10. 10.
    Zhang, Z.Q., Ye, Q., Li, Y.J.: Literature review on sentiment analysis of online product reviews. J. Manag. Sci. China 13(6), 84–96 (2010)Google Scholar
  11. 11.
    Zhang, H.Y., Ji, P., Wang, J.Q., Chen, X.H.: A novel decision support model for satisfactory restaurants utilizing social information: a case study of Tour. Manag. 59, 281–297 (2017)Google Scholar
  12. 12.
    Liu, Y., Bi, J.W., Fan, Z.P.: Ranking products through online reviews: a method based on sentiment analysis technique and intuitionistic fuzzy set theory. Inf. Fusion. 36, 149–161 (2017)Google Scholar
  13. 13.
    Levy, S.E., Duan, W.J., Boo, S.Y.: An analysis of one-star online reviews and responses in the Washington, D.C., lodging market. Cornell Hosp. Q. 54(1), 49–63 (2013)Google Scholar
  14. 14.
    Xu, H., Fan, Z.P., Liu, Y., Peng, W.L., Yu, Y.Y.: A method for evaluating service quality with hesitant fuzzy linguistic information. Int. J. Fuzzy Syst. 20(5), 1523–1538 (2018)Google Scholar
  15. 15.
    Kahraman, C., Onar, S.Ç., Öztayşi, B.: B2C marketplace prioritization using hesitant fuzzy linguistic AHP. Int. J. Fuzzy Syst. 20(7), 2202–2215 (2017)Google Scholar
  16. 16.
    Zhang, H.M.: Linguistic intuitionistic fuzzy sets and application in MAGDM. J. Appl. Math. 2014, 1–11 (2014)Google Scholar
  17. 17.
    Peng, H.G., Zhang, H.Y., Wang, J.Q.: Cloud decision support model for selecting hotels on with probabilistic linguistic information. Int. J. Hosp. Manag. 68, 124–138 (2018)Google Scholar
  18. 18.
    Bonferroni, C.: Sulle medie multiple di potenze. Bolletino dell`Unione Matematica Italiana 5, 267–270 (1950)MathSciNetzbMATHGoogle Scholar
  19. 19.
    Keshavarz, H., Abadeh, M.S.: ALGA: adaptive lexicon learning using genetic algorithm for sentiment analysis of microblogs. Knowl. Based Syst. 122, 1–16 (2017)Google Scholar
  20. 20.
    Singh, J.P., Irani, S., Rana, N.P., Dwivedi, Y.K., Saumya, S., Kumar Roy, P.: Predicting the “helpfulness” of online consumer reviews. J. Bus. Res. 70, 346–355 (2017)Google Scholar
  21. 21.
    Lau, R.Y.K., Zhang, W., Xu, W.: Parallel aspect-oriented sentiment analysis for sales forecasting with big data. Prod. Oper. Manag. 27(10), 1775–1794 (2018)Google Scholar
  22. 22.
    Fan, Z.P., Che, Y.J., Chen, Z.Y.: Product sales forecasting using online reviews and historical sales data: a method combining the Bass model and sentiment analysis. J. Bus. Res. 74, 90–100 (2017)Google Scholar
  23. 23.
    Khan, F.H., Qamar, U., Bashir, S.: SWIMS: semi-supervised subjective feature weighting and intelligent model selection for sentiment analysis. Knowl. Based Syst. 100, 97–111 (2016)Google Scholar
  24. 24.
    Agarwal, B., Poria, S., Mittal, N., Gelbukh, A., Hussain, A.: Concept-level sentiment analysis with dependency-based semantic parsing: a novel approach. Cogn. Comput. 7(4), 487–499 (2015)Google Scholar
  25. 25.
    Xia, Y., Cambria, E., Hussain, A., Zhao, H.: Word polarity disambiguation using bayesian model and opinion-level features. Cogn. Comput. 7(3), 369–380 (2014)Google Scholar
  26. 26.
    Guo, Y., Barnes, S.J., Jia, Q.: Mining meaning from online ratings and reviews: tourist satisfaction analysis using latent dirichlet allocation. Tour. Manag. 59, 467–483 (2017)Google Scholar
  27. 27.
    Loughran, T., Mcdonald, B.: When is a liability not a liability? Textual analysis, dictionaries, and 10-ks. J. Finance 66(1), 35–65 (2011)Google Scholar
  28. 28.
    Thompson, J.J., Leung, B.H.M., Blair, M.R., Taboada, M.: Sentiment analysis of player chat messaging in the video game StarCraft 2: extending a lexicon-based model. Knowl. Based Syst. 137, 149–162 (2017)Google Scholar
  29. 29.
    Liu, X., Singh, P.V., Srinivasan, K.: A structured analysis of unstructured big data by leveraging cloud computing. Market. Sci. 35(3), 363–388 (2016)Google Scholar
  30. 30.
    Chan, I.C.C., Lam, L.W., Chow, C.W.C., Fong, L.H.N., Law, R.: The effect of online reviews on hotel booking intention: the role of reader-reviewer similarity. Int. J. Hosp. Manag. 66, 54–65 (2017)Google Scholar
  31. 31.
    Sparks, B.A., So, K.K.F., Bradley, G.L.: Responding to negative online reviews: the effects of hotel responses on customer inferences of trust and concern. Tour. Manag. 53, 74–85 (2016)Google Scholar
  32. 32.
    Yang, C., Yu, X., Liu, Y., Nie, Y., Wang, Y.: Collaborative filtering with weighted opinion aspects. Neurocomputing 210(C), 185–196 (2016)Google Scholar
  33. 33.
    Scholz, M., Pfeiffer, J., Rothlauf, F.: Using PageRank for non-personalized default rankings in dynamic markets. Eur. J. Oper. Res. 260(1), 388–401 (2017)MathSciNetzbMATHGoogle Scholar
  34. 34.
    Fan, Z.P., Xi, Y., Liu, Y.: Supporting consumer’s purchase decision: a method for ranking products based on online multi-attribute product ratings. Soft. Comput. 22(16), 5247–5261 (2018)zbMATHGoogle Scholar
  35. 35.
    Saranya, T.: Mining features and ranking products from online customer reviews. Int. J. Eng. Res. Technol. 2(10), 643–648 (2013)Google Scholar
  36. 36.
    Yang, X., Yang, G., Wu, J.: Integrating rich and heterogeneous information to design a ranking system for multiple products. Decis. Support Syst. 84, 117–133 (2016)Google Scholar
  37. 37.
    Najmi, E., Hashmi, K., Malik, Z., Rezgui, A., Khan, H.U.: CAPRA: a comprehensive approach to product ranking using customer reviews. Computing 97(8), 843–867 (2015)MathSciNetGoogle Scholar
  38. 38.
    Ji, P., Zhang, H., Wang, J.: A fuzzy decision support model with sentiment analysis for items comparison in e-commerce: the case study of PConline. IEEE Trans. Syst. Man Cybernet. Syst. (2018). Google Scholar
  39. 39.
    Peng, Y., Kou, G., Li, J.: A fuzzy PROMETHEE approach for mining customer reviews in Chinese. Arab. J. Sci. Eng. 39(6), 5245–5252 (2014)Google Scholar
  40. 40.
    Delgado, M., Verdegay, J.L., Vila, M.A.: Linguistic decision-making models. Int. J. Intell. Syst. 7(5), 479–492 (1992)zbMATHGoogle Scholar
  41. 41.
    Xu, Z.S.: A method based on linguistic aggregation operators for group decision making with linguistic preference relations. Inf. Sci. 166(1–4), 19–30 (2004)MathSciNetzbMATHGoogle Scholar
  42. 42.
    Xu, Z.S.: A note on linguistic hybrid arithmetic averaging operator in multiple attribute group decision making with linguistic information. Group Decis. Negot. 15(6), 593–604 (2006)Google Scholar
  43. 43.
    Li, D., Liu, C., Gan, W.: A new cognitive model: cloud model. Int. J. Intell. Syst. 24(3), 357–375 (2009)zbMATHGoogle Scholar
  44. 44.
    Zhou, W., He, J.M.: Intuitionistic fuzzy normalized weighted Bonferroni mean and its application in multi-criteria decision making. J. Appl. Math. 1110-757x, 1–16 (2012)Google Scholar
  45. 45.
    Wang, J.Q., Wu, J.T., Wang, J., Zhang, H.Y., Chen, X.H.: Interval-valued hesitant fuzzy linguistic sets and their applications in multi-criteria decision-making problems. Inf. Sci. 288, 55–72 (2014)MathSciNetzbMATHGoogle Scholar
  46. 46.
    Wang, H., Feng, Y.: On multiple attribute group decision making with linguistic assessment information based on cloud model. Control Decis. 20(6), 679–685 (2005)Google Scholar
  47. 47.
    Wang, J., Peng, L., Zhang, H., Chen, X.: Method of multi-criteria group decision-making based on cloud aggregation operators with linguistic information. Inf. Sci. 274, 177–191 (2014)MathSciNetzbMATHGoogle Scholar
  48. 48.
    Peng, H.G., Wang, J.Q.: Cloud decision model for selecting sustainable energy crop based on linguistic intuitionistic information. Int. J. Syst. Sci. 48(15), 3316–3333 (2017)zbMATHGoogle Scholar
  49. 49.
    Wang, J., Peng, J., Zhang, H., Liu, T., Chen, X.: An uncertain linguistic multi-criteria group decision-making method based on a cloud model. Group Decis. Negot. 24(1), 171–192 (2014)Google Scholar
  50. 50.
    Wang, J.Q., Yang, W.E.: Multiple criteria group decision making method based on intuitionistic normal cloud by Monte Carlo simulation. Syst. Eng. Theory Pract. 33(11), 2859–2865 (2013)Google Scholar
  51. 51.
    Ma, H., Hu, Z.: Recommend trustworthy services using interval numbers of four parameters via cloud model for potential users. Front. Comput. Sci. 9(6), 887–903 (2015)Google Scholar
  52. 52.
    Peng, H.G., Wang, X.K., Wang, T.L., Wang, J.Q.: Multi-criteria game model based on the pairwise comparisons of strategies with Z-numbers. Appl. Soft Comput. 74, 451–465 (2019)Google Scholar
  53. 53.
    Peng, H.G., Wang, J.Q.: A multicriteria group decision-making method based on the normal cloud model with Zadeh’s Z-numbers. IEEE Transact. Fuzzy Syst. 26(6), 3246–3260 (2018)Google Scholar
  54. 54.
    Liang, R.X., Wang, J.Q., Li, L.: Multi-criteria group decision-making method based on interdependent inputs of single-valued trapezoidal neutrosophic information. Neural Comput. Appl. 30, 241–260 (2018)Google Scholar
  55. 55.
    Shannon, C.E.A.: A mathematical theory of communication. AT&T Technol. J. ACM Sigmob. Mob. Comput. Commun. Rev. 5(1), 3–55 (2001)MathSciNetGoogle Scholar
  56. 56.
    Chen, Z.C., Liu, P.H., Pei, Z.: An approach to multiple attribute group decision making based on linguistic intuitionistic fuzzy numbers. Int. J. Comput. Intell. Syst. 8(4), 747–760 (2015)Google Scholar
  57. 57.
    Liu, P.D., Qin, X.Y.: Power average operators of linguistic intuitionistic fuzzy numbers and their application to multiple-attribute decision making. J. Intell. Fuzzy Syst. 32(1), 1029–1043 (2017)MathSciNetzbMATHGoogle Scholar
  58. 58.
    Liu, P.D., Qin, X.Y.: Maclaurin symmetric mean operators of linguistic intuitionistic fuzzy numbers and their application to multiple-attribute decision-making. J. Exp. Theor. Artif. Intell. 29(6), 1173–1202 (2017)MathSciNetGoogle Scholar
  59. 59.
    Peng, H.G., Wang, J.Q., Cheng, P.F.: A linguistic intuitionistic multi-criteria decision-making method based on the Frank Heronian mean operator and its application in evaluating coal mine safety. Int. J. Mach. Learn. Cybernet. 9(6), 1053–1068 (2017)Google Scholar
  60. 60.
    Zhang, H.Y., Ji, P., Wang, J.Q., Chen, X.H.: A neutrosophic normal cloud and its application in decision-making. Cogn. Comput. 8(4), 649–669 (2016)Google Scholar

Copyright information

© Taiwan Fuzzy Systems Association 2019

Authors and Affiliations

  1. 1.School of BusinessCentral South UniversityChangshaChina

Personalised recommendations