Abstract
It is well known that human reasoning and decision-making are strongly influenced by psychological aspects. Recent works explore the adoption of personality traits to provide personalized recommendations. In this article, we report experimental results obtained with implicit recognition of Big Five personality traits from users’ text reviews. Hence, we present a personality-based recommender system with the analysis of the overall users’ satisfaction regarding the list of recommended items, showing promising results.
Keywords
- Text Review
- Personality-based Recommender Systems
- Personality Elicitation
- Linguistic Inquiry And Word Count (LIWC)
- Reviews Transcriptions
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Argamon, S., Dhawle, S., Koppel, M., Pennebaker, J.: Lexical predictors of personality type. In: Proceedings of the Joint Annual Meeting of the Interface and the Classification Society of North America, (2005)
Cantador, I., Fernandez-Tobas, I., Bellogn, A., Kosinski, M., Stillwell, D.: Relating personality types with user preferences in multiple entertainment domains. In: UMAP Workshops, Citeseer (2013)
Chen, J., Hsieh, G., Mahmud, J.U., Nichols, J.: Understanding individuals’ personal values from social media word use. In: Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work and Social Computing, pp. 405–414. ACM (2014)
Cremonesi, P., Garzotto, F., Turrin, R.: Investigating the persuasion potential of recommender systems from a quality perspective: an empirical study. ACM Trans. Interact. Intell. Syst. (TiiS) 2(2), 11 (2012)
Dunn, G., Wiersema, J., Ham, J., Aroyo, L.: Evaluating interface variants on personality acquisition for recommender systems. In: Houben, G.J., McCalla, G., Pianesi, F., Zancanaro, M. (eds.) User Modeling, Adaptation, and Personalization. Lecture Notes in Computer Science, vol. 5535, pp. 259–270. Springer, Berlin (2009)
Goldberg, L.R.: The development of markers for the big-five factor structure. Psychol. Assess. 4(1), 26 (1992)
Gonzalez, G., de la Rosa, J., Montaner, M., Delfin, S.: Embedding emotional context in recommender systems. In: IEEE 23rd International Conference on Data Engineering Workshop, pp. 845–852 (2007)
Hu, M., Liu, B.: Mining and summarizing customer reviews. In: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 168–177. ACM (2004)
Hu, R.: Design and user issues in personality-based recommender systems. In: Proceedings of the Fourth ACM Conference on Recommender Systems, vol. 10, pp. 357–360. ACM, New York, NY, USA (2010)
Hu, R., Pu, P.: A study on user perception of personality-based recommender systems. In: De Bra, P., Kobsa, A., Chin, D. (eds.) User Modeling, Adaptation, and Personalization. Lecture Notes in Computer Science, vol. 6075, pp. 291–302. Springer, Berlin (2010)
Iacobelli, F., Gill, A.J., Nowson, S., Oberlander, J.: Large scale personality classification of bloggers. In: Affective Computing and Intelligent Interaction, pp. 568–577. Springer (2011)
Lekakos, G., Giaglis, G.M.: Improving the prediction accuracy of recommendation algorithms: approaches anchored on human factors. Interact. Comput. 18(3), 410–431 (2006)
Lin, C.H., McLeod, D., et al.: Exploiting and learning human temperaments for customized information recommendation. In: IMSA, pp. 218–223 (2002a)
Mairesse, F., Walker, M.A., Mehl, M.R., Moore, R.K.: Using linguistic cues for the automatic recognition of personality in conversation and text. J. Artif. Intell. Res. 30(1), 457–500 (2007)
McCrae, R., Costa, P.: The Neo Personality Inventory Manual. Psychological Assessment Resources, Odessa (1985)
Norman, W.T.: Toward an adequate taxonomy of personality attributes: replicated factor structure in peer nomination personality ratings. J. Abnorm. Soc. Psychol. 66(6), 574 (1963)
Nunes, M.A.S., Hu, R.: Personality-based recommender systems: an overview. In: Proceedings of the Sixth ACM Conference on Recommender Systems, p. 56. ACM (2012)
Oberlander, J., Nowson, S.: Whose thumb is it anyway?: classifying author personality from weblog text. In: Proceedings of the COLING/ACL on Main Conference Poster Sessions, Association for Computational Linguistics, pp. 627–634 (2006)
Pazzani, M.: A framework for collaborative, content-based and demographic filtering. Artif. Intell. Rev. 13(5–6), 393–408 (1999)
Perik, E., De Ruyter, B., Markopoulos, P., Eggen, B.: The sensitivities of user profile information in music recommender systems. Proceedings of Private, Security, Trust, pp. 137–141 (2004)
Recio-Garcia, J.A., Jimenez-Diaz, G., Sanchez-Ruiz, A.A., Diaz-Agudo, B.: Personality aware recommendations to groups. In: Proceedings of the Third ACM Conference on Recommender Systems, pp. 325–328 ACM (2009)
Rentfrow, P.J., Gosling, S.D.: The do re mis of everyday life: the structure and personality correlates of music preferences. J. Personal. Soc. Psychol. 84(6), 1236 (2003)
Roshchina, A., Cardiff, J., Rosso, P.: A comparative evaluation of personality estimation algorithms for the twin recommender system. In: Proceedings of the 3rd International Workshop on Search and Mining User-Generated Contents, pp. 11–18. ACM (2011)
Triandis, H.C., Suh, E.M.: Cultural influences on personality. Annu. Rev. Psychol. 53(1), 133–160 (2002)
Zheng, N., Li, Q.: A recommender system based on tag and time information for social tagging systems. Expert Syst. Appl. 38(4), 45754587 (2011)
Acknowledgments
Special thanks to our participants for their cooperation.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Di Rienzo, A., Neishabouri, A. (2016). Recommendations with Personality Traits Extracted from Text Reviews. In: Novais, P., Camacho, D., Analide, C., El Fallah Seghrouchni, A., Badica, C. (eds) Intelligent Distributed Computing IX. Studies in Computational Intelligence, vol 616. Springer, Cham. https://doi.org/10.1007/978-3-319-25017-5_33
Download citation
DOI: https://doi.org/10.1007/978-3-319-25017-5_33
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25015-1
Online ISBN: 978-3-319-25017-5
eBook Packages: EngineeringEngineering (R0)