skip to main content
10.1145/3366030.3366098acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiiwasConference Proceedingsconference-collections
short-paper

Personality Estimation using Demographic Data in a Personality-based Recommender System: A Proposal

Published: 22 February 2020 Publication History

Abstract

Collaborative filtering in a recommender system has a weakness called cold start problem. One way to resolve this problem is by using personality traits that can be automatically predicted from the status that the users write in social media like Facebook and Twitter. The problem with this method is that a user of such system must have at least one account in at least one social media and must write at least one status with certain length. We propose to use the combination of personality traits and demographic data to overcome this problem. Previous studies reveal that personality traits are influenced by age and gender. By using these findings, we will build models to predict personality traits from such demographic data. The modeling will be conducted by means of classification and association rule methods. Novel domains will be used in the proposed system, namely sports and hobbies.

References

[1]
G Adomavicius and A Tuzhilin (2005). Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions. IEEE Transactions on Knowledge and Data Engineering, 17(6), 734--749.
[2]
R Hu and P Pu, Using Personality Information in Collaborative Filtering for New Users, https://pdfs.semanticscholar.org/60b9/893f2735a3bbaf6ded14a6271dc850d722c8.pdf.
[3]
M Tkalčič, M Kunaver, J Tasič and A Košir, Personality Based User Similarity Measure for a Collaborative Recommender System, https://www.researchgate.net/publication/228984904_Personality_based_user_similarity_measure_for_a_collaborative_recommender_system.
[4]
M Tkalčič and L Chen, 2015 Personality and Recommender System, Recommender Systems Handbook (2nd. ed.). Springer, New York, USA.
[5]
L Chen, W Wu, and L He (2013). How Personality Influences Users' Needs for Recommendation Diversity?. CHI 2013 Extended Abstracts.
[6]
G Kraaykamp and K van Eijck (2005). Personality, media preferences, and cultural participation, Personality and Individual Differences. Elsevier, 38, 1675--1688.
[7]
O Chausson, Assessing The Impact of Gender and Personality on Film Preferences, https://pdfs.semanticscholar.org/682f/92a3deedbed883b7fb7faac0f4f29fa46877.pdf.
[8]
R R McCrae and O P John (1992). An Introduction to the Five-Factor Model and its Applications. Journal of Personality, 60(2), 175--215.
[9]
M A S N Nunes (2008). Recommender Systems based on Personality Traits. Computer Science [cs]. Universite Montpellier II - Sciences et Techniques du Languedoc.
[10]
P J Rentfrow, L R Goldberg, and R Zilco (2011). Listening, Watching, and Reading: The Structure and Correlates of Entertainment Preferences. Journal of Personality, 79(2), 223--258.
[11]
B Ferwerda, M Graus, A Vall, M Tkalčič, and M Schedl (2016). The Influence of Users' Personality Traits on Satisfaction and Attractiveness of Diversified Recommendation Lists. Empire 2016.
[12]
F Lu and N Tintarev (2018). A Diversity Adjusting Strategy with Personality for Music Recommendation. IntRS Workshop October 2018.
[13]
B P Knijnenburg and M C Willemsen (2009). Understanding the Effect of Adaptive Preference Elicitation Methods on User Satisfaction of a Recommender System. RecSys '09.
[14]
G Shani and A Gunawardana, 2011 Evaluating Recommendation System, Recommender Systems Handbook (1st. ed.). Springer, New York, USA.
[15]
F D Davis, R P Bagozzi, and P R Warshaw (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982--1003.
[16]
C. J. Soto, O. P. John, S. D. Gosling, and J. Potter. Age Differences in Personality Traits From 10 to 65: Big Five Domains and Facets in a Large Cross-Sectional Sample. Journal of Personality and Social Psychology, 100(2), 330--348.
[17]
M. A. Harris and C. E. Brett (2016). Personality Stability From Age 14 to Age 77 Years. Psychology and Aging, 31(8), 862--874.
[18]
P. Martin, M. V. Long, and L. W. Poon (2002). Age Changes and Differences in Personality Traits and States of the Old and Very Old. Journal of Gerontology, 57B(2), 144--152.
[19]
M. D. Giudice, T. Booth, and P. Irwing (2012). The Distance Between Mars and Venus: Measuring Global Sex Differences in Personality. PLoS ONE, 7(1), 1--8.
[20]
S. C. South, A. M. Jarnecke, and C. E. Vize (2018). Sex differences in the Big Five model personality traits: A behavior genetics exploration. Journal of Research in Personality, 74, 158--165.
[21]
Y. J. Weisberg, C. G. DeYoung, and J. B. Hirsh (2011). Gender differences in personality across the ten aspects of the Big Five. Fronties in Psychology, 2, 1--11.
[22]
P. T. Costa Jr., A. Terracciano, and R. R. McCrae (2001). Gender Differences in Personality Traits Across Cultures: Robust and Surprising Findings. Journal of Personaltiy and Social Psychology, 81(2), 322--331.
[23]
D. P. Schmitt, A. E. Long, A. McPhearson, K. O'Brien, B. Remmert, and S. H. Shah (2017). Personality and gender differences in global perspective. International Journal of Psychology, 52(S1), 45--46.
[24]
M. F. Radwan, The psychology of hobbies (The connection between hobbies and personalities), https://www.2knowmyself.com/The_psychology_of_hobbies.
[25]
X. Tran (2012). Footbal Scores on the Big Five Personality Factors across 50 States in the U.S. Journal of Sports Medicine & Doping Studies, 2(6), 1--5.
[26]
P. Steca, D. Baretta, A. Greco, M. D'Addario, and D. Monzani (2018). Associations between personality, sports participation and athletic success. A comparison of Big Five in sporting and non-sporting adults. Personality and Individual Differences, 121, 176--183.
[27]
U. Dobersek and C. Bartling (2008). Connection between Personality Type and Sports. American Jounal of Psychological Research, 4(1), 21--28.
[28]
D. J. Rhea and S. Martin (2010). Personality Trait Differences of Traditional Sport Athletes, Builders, and Other Alternative Sport Athletes. International Journal of Sports Science & Coaching, 5(1), 75--85.
[29]
Lingokids, List of Sports, https://www.lingokids.com/english-for-kids/list-of-sports.
[30]
Local Adventurer, 101 Hobbies to Start in 2019 - Listed by Types of Hobbies, https://localadventurer.com/types-of-hobbies/.
[31]
P. Pu, L. Chen, and R. Hu (2011). A User-Centric Evaluation Framework for Recommender Systems. RecSys'11, Chicago, Illinois, USA.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
iiWAS2019: Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services
December 2019
709 pages
Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

In-Cooperation

  • JKU: Johannes Kepler Universität Linz
  • @WAS: International Organization of Information Integration and Web-based Applications and Services

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 February 2020

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Association Rule
  2. Big Five
  3. Classification Method
  4. Decision Tree
  5. Demographic Data
  6. Five Factor Model
  7. Naïve Bayes
  8. Personality Traits
  9. Recommender System for Hobbies
  10. Recommender System for Sports
  11. k-Nearest Neighbor

Qualifiers

  • Short-paper
  • Research
  • Refereed limited

Conference

iiWAS2019

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 151
    Total Downloads
  • Downloads (Last 12 months)7
  • Downloads (Last 6 weeks)2
Reflects downloads up to 17 Feb 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media