508
Views
1
CrossRef citations to date
0
Altmetric
Research Articles

Ranking products through online reviews: A novel data-driven method based on interval type-2 fuzzy sets and sentiment analysis

, , &
Pages 860-873 | Received 30 Apr 2022, Accepted 10 May 2023, Published online: 25 May 2023

References

  • Al-Smadi, M., Qawasmeh, O., Al-Ayyoub, M., Jararweh, Y., & Gupta, B. (2018). Deep recurrent neural network vs. support vector machine for aspect-based sentiment analysis of Arabic hotels’ reviews. Journal of Computational Science, 27, 386–393. https://doi.org/10.1016/j.jocs.2017.11.006
  • Bi, J., Liu, Y., & Fan, Z. (2019). Representing sentiment analysis results of online reviews using interval type-2 fuzzy numbers and its application to product ranking. Information Sciences, 504, 293–307. https://doi.org/10.1016/j.ins.2019.07.025
  • Bi, J., Liu, Y., Fan, Z., & Cambria, E. (2019). Modelling customer satisfaction from online reviews using ensemble neural network and effect-based Kano model. International Journal of Production Research, 57(22), 7068–7088. https://doi.org/10.1080/00207543.2019.1574989
  • Bi, J., Liu, Y., Fan, Z., & Zhang, J. (2019). Wisdom of crowds: Conducting importance-performance analysis (ipa) through online reviews. Tourism Management, 70, 460–478. https://doi.org/10.1016/j.tourman.2018.09.010
  • Chen, T. (2013). A linear assignment method for multiple-criteria decision analysis with interval type-2 fuzzy sets. Applied Soft Computing, 13(5), 2735–2748. https://doi.org/10.1016/j.asoc.2012.11.013
  • Cosguner, K., & Seetharaman, P. B. S. (2022). Dynamic pricing for new products using a utility-based generalization of the bass diffusion model. Management Science, 68(3), 1904–1922. https://doi.org/10.1287/mnsc.2021.4257
  • Darko, A. P., & Liang, D. (2023). A heterogeneous opinion-driven decision-support model for tourists’ selection with different travel needs in online reviews. Journal of the Operational Research Society, 74(1), 272–289. https://doi.org/10.1080/01605682.2022.2035274
  • Fan, Z., Li, G., & Liu, Y. (2020). Processes and methods of information fusion for ranking products based on online reviews: An overview. Information Fusion, 60, 87–97. https://doi.org/10.1016/j.inffus.2020.02.007
  • Fu, X., Liu, G., Guo, Y., & Wang, Z. (2013). Multi-aspect sentiment analysis for Chinese online social reviews based on topic modeling and HowNet lexicon. Knowledge-Based Systems, 37, 186–195. https://doi.org/10.1016/j.knosys.2012.08.003
  • Gandhi, A., Adhvaryu, K., Poria, S., Cambria, E., & Hussain, A. (2023). Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions. Information Fusion, 91, 424–444. https://doi.org/10.1016/j.inffus.2022.09.025
  • Gomes, L. F. A. M., & Lima, M. M. (1991). TODIM: Basic and application to multicriteria ranking of projects with environmental impacts. Foundations of Computing and Decision Sciences, 16(3), 113–127.
  • Guo, C., Du, Z., & Kou, X. (2018). Products ranking through aspect-based sentiment analysis of online heterogeneous reviews. Journal of Systems Science and Systems Engineering, 27(5), 542–558. https://doi.org/10.1007/s11518-018-5388-2
  • Hu, J., Zhang, Y., Chen, X., & Liu, Y. (2013). Multi-criteria decision making method based on possibility degree of interval type-2 fuzzy number. Knowledge-Based Systems, 43, 21–29. https://doi.org/10.1016/j.knosys.2012.11.007
  • Jiang, L., Li, Y., Liao, J., Zou, Z., & Jiang, C. (2023). Research on non-dependent aspect-level sentiment analysis. Knowledge-Based Systems, 266, 110419. https://doi.org/10.1016/j.knosys.2023.110419
  • Jin, J., Jia, D., & Chen, K. (2022). Mining online reviews with a Kansei-integrated Kano model for innovative product design. International Journal of Production Research, 60(22), 6708–6727. https://doi.org/10.1080/00207543.2021.1949641
  • Joung, J., & Kim, H. M. (2022). Explainable neural network-based approach to Kano categorisation of product features from online reviews. International Journal of Production Research, 60(23), 7053–7073. https://doi.org/10.1080/00207543.2021.2000656
  • Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185
  • Karasakal, E., Eryılmaz, U., & Karasakal, O. (2022). Ranking using PROMETHEE when weights and thresholds are imprecise: A data envelopment analysis approach. Journal of the Operational Research Society, 73(9), 1978–1995. https://doi.org/10.1080/01605682.2021.1963195
  • Karnik, N. N., & Mendel, J. M. (2001). Centroid of a type-2 fuzzy set. Information Sciences, 132(1–4), 195–220. https://doi.org/10.1016/S0020-0255(01)00069-X
  • Kim, Y. (2014). Convolutional neural networks for sentence classification. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (pp. 1746–1751). Association for Computational Linguistics.
  • Kim, J. J., & Han, H. (2022). Saving the hotel industry: Strategic response to the COVID-19 pandemic, hotel selection analysis, and customer retention. International Journal of Hospitality Management, 102, 103163. https://doi.org/10.1016/j.ijhm.2022.103163
  • Kraus, M., Feuerriegel, S., & Oztekin, A. (2020). Deep learning in business analytics and operations research: Models, applications and managerial implications. European Journal of Operational Research, 281(3), 628–641. https://doi.org/10.1016/j.ejor.2019.09.018
  • Leoneti, A. B., & Gomes, L. F. A. M. (2021). A novel version of the TODIM method based on the exponential model of prospect theory: The ExpTODIM method. European Journal of Operational Research, 295(3), 1042–1055. https://doi.org/10.1016/j.ejor.2021.03.055
  • Liu, Y., Bi, J., & Fan, Z. (2017). A method for multi-class sentiment classification based on an improved one-vs-one (ovo) strategy and the support vector machine (svm) algorithm. Information Sciences, 394–395, 38–52. https://doi.org/10.1016/j.ins.2017.02.016
  • Liu, Y., Bi, J., & Fan, Z. (2017). Ranking products through online reviews: A method based on sentiment analysis technique and intuitionistic fuzzy set theory. Information Fusion, 36(36), 149–161. https://doi.org/10.1016/j.inffus.2016.11.012
  • Liu, Y., Fan, Z., & Zhang, X. (2016). A method for large group decision-making based on evaluation information provided by participators from multiple groups. Information Fusion, 29, 132–141. https://doi.org/10.1016/j.inffus.2015.08.002
  • Liu, X., & Mendel, J. M. (2011). Connect karnik-mendel algorithms to root-finding for computing the centroid of an interval type-2 fuzzy set. IEEE Transactions on Fuzzy Systems, 19(4), 652–665. https://doi.org/10.1109/TFUZZ.2011.2130528
  • Mendel, J. M., & John, R. B. (2002). Type-2 fuzzy sets made simple. IEEE Transactions on Fuzzy Systems, 10(2), 117–127. https://doi.org/10.1109/91.995115
  • Park, J., & Lee, B. K. (2021). An opinion-driven decision-support framework for benchmarking hotel service. Omega, 103, 102415. https://doi.org/10.1016/j.omega.2021.102415
  • Qin, J., Liu, X., & Pedrycz, W. (2017). An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment. European Journal of Operational Research, 258(2), 626–638. https://doi.org/10.1016/j.ejor.2016.09.059
  • Qin, J., & Zeng, M. (2022). An integrated method for product ranking through online reviews based on evidential reasoning theory and stochastic dominance. Information Sciences, 612, 37–61. https://doi.org/10.1016/j.ins.2022.08.070
  • Ren, P., Zhu, B., Ren, L., & Ding, N. (2022). Online choice decision support for consumers: Data-driven analytic hierarchy process based on reviews and feedback. Journal of the Operational Research Society, 1–14. https://doi.org/10.1080/01605682.2022.2129491
  • Sang, X., & Liu, X. (2016). An interval type-2 fuzzy sets-based TODIM method and its application to green supplier selection. Journal of the Operational Research Society, 67(5), 722–734. https://doi.org/10.1057/jors.2015.86
  • Srivastava, P. R., Eachempati, P., Charles, V., & Rana, N. P. (2022). A hybrid machine learning approach to hotel sales rank prediction. Journal of the Operational Research Society, 1–17. https://doi.org/10.1080/01605682.2022.2096498
  • Walczak, D., & Rutkowska, A. (2017). Project rankings for participatory budget based on the fuzzy TOPSIS method. European Journal of Operational Research, 260(2), 706–714. https://doi.org/10.1016/j.ejor.2016.12.044
  • Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
  • Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning—I. Information Sciences, 8(3), 199–249. https://doi.org/10.1016/0020-0255(75)90036-5
  • Zhang, D., Li, Y., & Wu, C. (2020). An extended TODIM method to rank products with online reviews under intuitionistic fuzzy environment. Journal of the Operational Research Society, 71(2), 322–334. https://doi.org/10.1080/01605682.2018.1545519
  • Zhang, D., Wu, C., & Liu, J. (2020). Ranking products with online reviews: A novel method based on hesitant fuzzy set and sentiment word framework. Journal of the Operational Research Society, 71(3), 528–542. https://doi.org/10.1080/01605682.2018.1557021
  • Zhang, Z., Yang, K., Zhang, J., & Palmatier, R. W. (2023). Uncovering synergy and dysergy in consumer reviews: A machine learning approach. Management Science, 69(4), 2339–2360. https://doi.org/10.1287/mnsc.2022.4443
  • Zuheros, C., Martínez-Cámara, E., Herrera-Viedma, E., & Herrera, F. (2021). Sentiment analysis based multi-person multi-criteria decision making methodology using natural language processing and deep learning for smarter decision aid. Case study of restaurant choice using TripAdvisor reviews. Information Fusion, 68, 22–36. https://doi.org/10.1016/j.inffus.2020.10.019

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.