International Journal of Education and Management Engineering(IJEME)

ISSN: 2305-3623 (Print), ISSN: 2305-8463 (Online)

Published By: MECS Press

IJEME Vol.8, No.2, Mar. 2018

An Enhanced Approach for Quantitative Prediction of Personality in Facebook Posts

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Azhar Imran, Muhammad Faiyaz, Faheem Akhtar

Index Terms

Personality Prediction;Psychological Personality Traits;Sentiment Analysis;Social Media


Social media is a collection of computer-mediated technologies that encourages the creation and sharing of data, thoughts and vocation interests by means of online communities. There are various kinds of web-based social networking i.e. micro-blogs, wikis and social networking sites. Different social media like Facebook, LinkedIn, Google+ and Twitter are the popular sources for connecting people all over the globe. Facebook is one of the commonly used platform where individual’s used to stay in touch, business personnel used for marketing and others used to share expedient information. Due to this lucrative nature, one’s personality can be predicted on the basis of posts created, commented on others post and likes against any posts.  We have developed in-house tool using python language that defines personality in terms of psychological model of Big-5 personality traits including extraversion, neuroticism, agreeableness, openness and conscientiousness. The dictionary based approach has been used in this tool in which we have combined three dictionaries (WordNet, SenticNet and Opinion Lexicon). Our proposed technique has shown promising results as we have analyzed 213 unique Facebook profiles and their results outperforms the others. Furthermore a comparative analysis of machine learning classifiers i.e. support vector machine, na?ve bays and decision tree has performed. Our approach succeeds to predict personality traits. We are intended to predict personality from roman English posts in future.

Cite This Paper

Azhar Imran, Muhammad Faiyaz, Faheem Akhtar,"An Enhanced Approach for Quantitative Prediction of Personality in Facebook Posts", International Journal of Education and Management Engineering(IJEME), Vol.8, No.2, pp.8-19, 2018.DOI: 10.5815/ijeme.2018.02.02


[1]Van der Geer J, Hanraads JAJ, Lupton RA. The art of writing a scientific article. J Sci Commun 2000; 163:51-9.

[2]Obar, J. A., & Wildman, S. S. (2015). Social media definition and the governance challenge: An introduction to the special issue.

[3]Kietzmann, J. H., Hermkens, K., McCarthy, I. P., & Silvestre, B. S. (2011). Social media? Get serious! Understanding the functional building blocks of social media. Business horizons, 54(3), 241-251.

[4]Kuei-Hsiang, P., & Li-Heng, L. (2015). Predicting personality traits of Chinese users based on Facebook wall posts. Wireless and Optical Communication Conference (WOCC), 2015. 

[5]Kr?mer, N. C., & Winter, S. (2008). Impression management 2.0.The relationship of self-esteem, extraversion, self-efficacy, and self-presentation within social networking sites. Journal of Media Psychology, 20(3): (pp. 106-112).

[6]Quercia, D., Lambiotte, R., Stillwell, D., Kosinski, M., & Crowcroft, J. (2012). The personality of popular Facebook users. In Proceedings of the ACM 2012 conference on Computer Supported `32Cooperative Work, (pp. 955–964). ACM.

[7]Farnadi, G., Sitaraman, G., Sushmita, S., Celli, F., Kosinski, M., & Stillwell, D. (2016, June). Computational personality recognition in social media, user modeling and user-adapted interaction. June 2016, Volume 26, Issue 2, (pp. 109–142).

[8]Farnadi, G., Zoghbi, S., Moens, M., & De Cock, M. (2013). Recognising personality traits using Facebook status updates. In: Proceedings of the WCPR, (pp. 14–18).

[9]Quercia, D., Kosinski, M., Stillwell, D., & Crowcroft, J. (2011). Our Twitter profiles, our selves: predicting personality with Twitter. In: Privacy, Security, Risk and Trust (passat), 2011 IEEE Third International Conference on Social Computing (socialcom), (pp. 180–185). IEEE.  


[11]Hsu, C. W., Chang, C. C., & Lin, C. J. (2003). A practical guide to support vector classification.

[12]Rish, I. (2001, August). An empirical study of the naive Bayes classifier. In IJCAI 2001 workshop on empirical methods in artificial intelligence (Vol. 3, No. 22, pp. 41-46). IBM.


[14]Cambria, E. (2016). Affective computing and sentiment analysis. IEEE Intelligent Systems,      31(2), 102-107.

[15]Ikonomakis, M., Kotsiantis, S., & Tampakas,V. (2005). Text classification using machine learning techniques. WSEAS Transaction on Computers, 8(4), 966-974.

[16]Golbeck, J., Robles, C., Edmondson, M., & Turner, K. (2011, October). Predicting personality from twitter. In Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE Third Inernational Conference on Social Computing (SocialCom), 2011 IEEE Third International Conference on (pp. 149-156). IEEE.

[17]Chen, T. Y., Chen, T. Y., Tsai, M. C., Tsai, M. C., Chen, Y. M., & Chen, Y. M. (2016). A user’s personality prediction approach by mining network interaction behaviors on Facebook. Online Information Review, 40(7), 913-937.

[18]Salton, G., & Buckley, C. (1988). Term-weighting approaches  in automatic  text  retrieval.  Information Processing  and Management, 24(5),  513-523,  1988.

[19]Google Search Statistics. (2016, January 10). Retrieved from website:

[20]Vinay K. Jain, Shishir Kumar, "Towards Prediction of Election Outcomes Using Social Media", International Journal of Intelligent Systems and Applications(IJISA), Vol.9, No.12, pp.20-28, 2017. DOI: 10.5815/ijisa.2017.12.03

[21]Asad Mehmood, Abdul S. Palli, M.N.A. Khan,"A Study of Sentiment and Trend Analysis Techniques for Social Media Content", IJMECS, vol.6, no.12, pp.47-54, 2014.DOI: 10.5815/ijmecs.2014.12.07

[22]Ibtesam Fares. Al-Mashaqbeh,"Facebook Applications to Promote Academic Engagement: Student's Attitudes towards the Use of Facebook as a Learning Tool", IJMECS, vol.7, no.11, pp.60-66, 2015.DOI: 10.5815/ijmecs.2015.11.07.

[23]Waters, Richard D., et al. "Engaging stakeholders through social networking: How nonprofit organizations are using Facebook." Public relations review 35.2 (2009): 102-106.

[24]Courtney, K. L. "The use of social media in healthcare: organizational, clinical, and patient perspectives." Enabling health and healthcare through ICT: available, tailored and closer 183 (2013): 244.

[25]Zhang, Jie, Yongjun Sung, and Wei-Na Lee. "To play or not to play: An exploratory content analysis of branded entertainment in Facebook." American Journal of Business25.1 (2010): 53-64.

[26]Elmore, Kimberly L., et al. "mPING: Crowd-sourcing weather reports for research." Bulletin of the American Meteorological Society 95.9 (2014): 1335-1342.

[27]Sanderson, Jimmy. "From loving the hero to despising the villain: Sports fans, Facebook, and social identity threats." Mass Communication and Society 16.4 (2013): 487-509.

[28]Imran, A., W. Aslam, and M.I. Ullah. "Quantitative Prediction of Offensiveness using Text Mining of Twitter Data." Sindh University Research Journal-SURJ (Science Series) 49.1 (2017).