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An In-Depth Analysis of Personality Prediction

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ICT Innovations 2019. Big Data Processing and Mining (ICT Innovations 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1110))

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Abstract

The complex nature of human mind poses recurrent challenges for predictive modeling of human traits and behavior and current technological trends has real potential for advancing the endeavor. In this paper, we present an in-depth analysis of the suitability and effectiveness of several personality prediction models, that incorporate both, multimodal and linguistic features. By studying the impact of various modeling decisions on the predictivness of each Big Five personality dimension, our findings suggest that some modeling choices might be at odds with one another or the objective of the target application scenario, which highlights the importance of extensive experimentation and unique modeling approaches for various aspects of this multi-faceted phenomenon.

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Notes

  1. 1.

    https://www.idiap.ch/dataset/youtube-personality.

  2. 2.

    https://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html#lexicon.

  3. 3.

    https://github.com/aesuli/SentiWordNet.

  4. 4.

    https://saifmohammad.com/WebPages/AffectIntensity.htm.

  5. 5.

    https://saifmohammad.com/WebPages/nrc-vad.html.

  6. 6.

    https://github.com/Ejhfast/empath-client.

  7. 7.

    http://www.wjh.harvard.edu/~inquirer/spreadsheet_guide.htm.

  8. 8.

    http://liwc.wpengine.com/.

References

  1. Harvard inquirer. http://www.wjh.harvard.edu/~inquirer/

  2. Baccianella, S., Esuli, A., Sebastiani, F.: Sentiwordnet 3.0: an enhanced lexical resource for sentiment analysis and opinion mining. In: Lrec, vol. 10, pp. 2200–2204 (2010)

    Google Scholar 

  3. Biel, J.I., Gatica-Perez, D.: The YouTube lens: crowdsourced personality impressions and audiovisual analysis of vlogs. IEEE Trans. Multimedia 15(1), 41–55 (2013)

    Article  Google Scholar 

  4. Biel, J.I., Tsiminaki, V., Dines, J., Gatica-Perez, D.: Hi YouTube!: personality impressions and verbal content in social video. In: Proceedings of the 15th ACM on International Conference on Multimodal Interaction, pp. 119–126. ACM (2013)

    Google Scholar 

  5. Celli, F., Lepri, B., Biel, J.I., Gatica-Perez, D., Riccardi, G., Pianesi, F.: The workshop on computational personality recognition 2014. In: Proceedings of the 22nd ACM International Conference on Multimedia, pp. 1245–1246. ACM (2014)

    Google Scholar 

  6. Celli, F., Pianesi, F., Stillwell, D., Kosinski, M.: Workshop on computational personality recognition: shared task. In: Seventh International AAAI Conference on Weblogs and Social Media (2013)

    Google Scholar 

  7. Coltheart, M.: The MRC psycholinguistic database. Q. J. Exp. Psychol. Sect. A 33(4), 497–505 (1981)

    Article  Google Scholar 

  8. Fast, E., Chen, B., Bernstein, M.S.: Empath: understanding topic signals in large-scale text. In: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pp. 4647–4657. ACM (2016)

    Google Scholar 

  9. Gievska, S., Koroveshovski, K.: The impact of affective verbal content on predicting personality impressions in YouTube videos. In: Proceedings of the 2014 ACM Multi Media on Workshop on Computational Personality Recognition, pp. 19–22. ACM (2014)

    Google Scholar 

  10. Gievska, S., Koroveshovski, K., Chavdarova, T.: A hybrid approach for emotion detection in support of affective interaction. In: 2014 IEEE International Conference on Data Mining Workshop, pp. 352–359. IEEE (2014)

    Google Scholar 

  11. John, O.P., Srivastava, S., et al.: The Big Five trait taxonomy: history, measurement, and theoretical perspectives. Handb. Pers. Theor. Res. 2(1999), 102–138 (1999)

    Google Scholar 

  12. Liu, B., Hu, M., Cheng, J.: Opinion observer: analyzing and comparing opinions on the web. In: Proceedings of the 14th International Conference on World Wide Web, pp. 342–351. ACM (2005)

    Google Scholar 

  13. 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, 457–500 (2007)

    Article  Google Scholar 

  14. Majumder, N., Poria, S., Gelbukh, A., Cambria, E.: Deep learning-based document modeling for personality detection from text. IEEE Intell. Syst. 32(2), 74–79 (2017)

    Article  Google Scholar 

  15. Markovikj, D., Gievska, S., Kosinski, M., Stillwell, D.J.: Mining facebook data for predictive personality modeling. In: Seventh International AAAI Conference on Weblogs and Social Media (2013)

    Google Scholar 

  16. Mehl, M.R., Gosling, S.D., Pennebaker, J.W.: Personality in its natural habitat: manifestations and implicit folk theories of personality in daily life. J. Pers. Soc. Psychol. 90(5), 862 (2006)

    Article  Google Scholar 

  17. Miller, G.A.: WordNet: a lexical database for English. Commun. ACM 38(11), 39–41 (1995)

    Article  Google Scholar 

  18. Mohammad, S.: Obtaining reliable human ratings of valence, arousal, and dominance for 20,000 English words. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), vol. 1, pp. 174–184 (2018)

    Google Scholar 

  19. Mohammad, S.M.: Word affect intensities. arXiv preprint arXiv:1704.08798 (2017)

  20. Mohammad, S.M., Kiritchenko, S.: Using nuances of emotion to identify personality. In: Proceedings of ICWSM (2013)

    Google Scholar 

  21. Myers, I.B., McCaulley, M.H., Quenk, N.L., Hammer, A.L.: MBTI Manual: A Guide to the Development and Use of the Myers-Briggs Type Indicator, vol. 3. Consulting Psychologists Press, Palo Alto (1998)

    Google Scholar 

  22. Oberlander, J., Gill, A.J.: Individual differences and implicit language: personality, parts-of-speech and pervasiveness. In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol. 26 (2004)

    Google Scholar 

  23. Oberlander, J., Gill, A.J.: Language with character: a stratified corpus comparison of individual differences in e-mail communication. Discourse Process. 42(3), 239–270 (2006)

    Article  Google Scholar 

  24. Pennebaker, J.W., Francis, M.E., Booth, R.J.: Linguistic inquiry and word count: LIWC 2001. Mahway: Lawrence Erlbaum Associates 71(2001), 2001 (2001)

    Google Scholar 

  25. Pennebaker, J.W., King, L.A.: Linguistic styles: language use as an individual difference. J. Pers. Soc. Psychol. 77(6), 1296 (1999)

    Article  Google Scholar 

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Acknowledgements

This work was partially financed by the Faculty of Computer Science and Engineering at the “Ss. Cyril and Methodius” University.

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Authors and Affiliations

  1. Faculty of Computer Science and Engineering, ul.Rudzer Boshkovikj 16, P.O. 393, 1000, Skopje, Republic of North Macedonia

    Filip Despotovski & Sonja Gievska

Authors
  1. Filip Despotovski
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  2. Sonja Gievska
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Correspondence to Filip Despotovski .

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Editors and Affiliations

  1. Saints Cyril and Methodius University of Skopje, Skopje, North Macedonia

    Sonja Gievska

  2. Saints Cyril and Methodius University of Skopje, Skopje, North Macedonia

    Gjorgji Madjarov

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Despotovski, F., Gievska, S. (2019). An In-Depth Analysis of Personality Prediction. In: Gievska, S., Madjarov, G. (eds) ICT Innovations 2019. Big Data Processing and Mining. ICT Innovations 2019. Communications in Computer and Information Science, vol 1110. Springer, Cham. https://doi.org/10.1007/978-3-030-33110-8_12

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  • DOI: https://doi.org/10.1007/978-3-030-33110-8_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33109-2

  • Online ISBN: 978-3-030-33110-8

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