panel

Opportunities and risks of discovering personality traits from social media

Authors:

Michelle X. Zhou,

Jeffrey Nichols,

Jennifer Golbeck,

James W. PennebakerAuthors Info & Claims

CHI EA '14: CHI '14 Extended Abstracts on Human Factors in Computing Systems

Pages 1081 - 1086

https://doi.org/10.1145/2559206.2579408

Published: 26 April 2014 Publication History

Abstract

With the emergence of social media and the availability of big data, there has been much interest in mining the digital footprints left by users to predict personality traits (e.g., introvert and idealistic) and gain a deeper understanding of individuals. While such understanding will enable hyper-personalized computing, such as personality-based marketing, the use of this technology will have far-reaching social implications that could affect almost every aspect of our lives. For example, personality traits mined from social media could be used to guide hiring and promotion decisions or decide who is admitted into top academic programs. The risks of using derived personality traits are potentially high, particular due to factors such as the veracity of data collected from social media, imperfections in prediction algorithms, and a lack of control over how, when, and to whom anyone's personality traits might be exposed. We will use this panel to bring together experts from the fields of Psychology, Social Science, Computer Science, along with the CHI community, to discuss and debate the opportunities and risks of personality discovery from social media and the implications on technical communities and our society at large.

References

[1]

Chen, J., Hshieh, G., Mahmud, J. and Nichols, J. Understanding Individuals' Personal Values with Social Media Word Uses, Proc. CSCW '14. To appear.

Digital Library

[2]

Ford, K., Brands Laid Bare, Wiley, 2005.

[3]

Gilbert, G., and Karahalios, K. Predicting tie strength with social media. CHI 2009:211--220.

Digital Library

[4]

Golbeck, J., Robles, C., Edmondson, M., and Turner, K. (2011). Predicting personality from twitter. In IEEE Social Computing, 149--156.

[5]

Gou, L, Zhou, M. X., and Yang, H. KnowMe and ShareMe: Understanding Personality Traits Derived from Social Media and User Privacy Preferences. CHI 2014. Conditionally Accepted.

Digital Library

[6]

Mahmud, J., Zhou, M. X., Megiddo, N., Nichols, J., and Drews, C. Recommending Targeted Strangers from Whom to Solicit Information on Social Media, Proc. IUI 2013, 37--48.

Digital Library

[7]

Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370--96.

[8]

Pennacchiotti, M., Popescu, A. M. 2011. A Machine Learning Approach to Twitter User Classification, In Proc. ICWSM 2011.

[9]

Schwartz, S. H. (2006). Basic human values: Theory, measurement, and applications. Revue française de sociologie.

[10]

Tausczik, R. and Pennebaker, J. 2010. The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods, J. of Lang. and Social Psychology 29(1) 24--54.

[11]

Yang, H. and Li, Y. Identifying User Needs from Social Media. IBM Tech Report. goo.gl/2XB7NY

[12]

Yarkoni, Tal. 2010. Personality in 100,000 words: A largescale analysis of personality and word usage among bloggers. Journal of Research in Personality.

[13]

http://venturebeat.com/2013/10/08/ibm-researcher-can-decipher-your-personality-in-200-tweets/

[14]

http://www.technologyreview.com/news/520671/ads-could-soon-know-if-youre-an-introvert-on-twitter/

[15]

http://www.dailymail.co.uk/news/article-2508757/Employers-use-personality-profiling-technology-analyse-tweets.html

Cited By

Mukta MAntu BAzad NAbedeen IIslam N(2024)Analysis of Software Developers' Programming Language Preferences and Community Behavior From Big5 Personality TraitsSoftware: Practice and Experience10.1002/spe.338155:3(473-490)Online publication date: 14-Oct-2024
https://doi.org/10.1002/spe.3381
Alexander EVanathi RDhikhi TSowmiya M(2018)Privacy Shield securing privacy in social networks2018 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)10.1109/ICCIC.2018.8782322(1-4)Online publication date: Dec-2018
https://doi.org/10.1109/ICCIC.2018.8782322
Kokciyan NYolum P(2016)PriGuardIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2016.258342528:10(2724-2737)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1109/TKDE.2016.2583425
Show More Cited By

Index Terms

Opportunities and risks of discovering personality traits from social media
1. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

cover image ACM Conferences

CHI EA '14: CHI '14 Extended Abstracts on Human Factors in Computing Systems

April 2014

2620 pages

ISBN:9781450324748

DOI:10.1145/2559206

General Chairs:
Matt Jones
Swansea University, Wales, UK
,
Philippe Palanque
Université Paul Sabatier, France
,
Program Chairs:
Albrecht Schmidt
University of Stuttgart, Germany
,
Tovi Grossman
Autodesk Research, Canada

Copyright © 2014 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 April 2014

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CHI '14

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SIGCHI

CHI '14: CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2014

Ontario, Toronto, Canada

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CHI EA '14 Paper Acceptance Rate 1,000 of 3,200 submissions, 31%;

Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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CHI 2025

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ACM CHI Conference on Human Factors in Computing Systems

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Cited By

Mukta MAntu BAzad NAbedeen IIslam N(2024)Analysis of Software Developers' Programming Language Preferences and Community Behavior From Big5 Personality TraitsSoftware: Practice and Experience10.1002/spe.338155:3(473-490)Online publication date: 14-Oct-2024
https://doi.org/10.1002/spe.3381
Alexander EVanathi RDhikhi TSowmiya M(2018)Privacy Shield securing privacy in social networks2018 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)10.1109/ICCIC.2018.8782322(1-4)Online publication date: Dec-2018
https://doi.org/10.1109/ICCIC.2018.8782322
Kokciyan NYolum P(2016)PriGuardIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2016.258342528:10(2724-2737)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1109/TKDE.2016.2583425
Hekler EMichie SPavel MRivera DCollins LJimison HGarnett CParral SSpruijt-Metz D(2016)Advancing Models and Theories for Digital Behavior Change InterventionsAmerican Journal of Preventive Medicine10.1016/j.amepre.2016.06.01351:5(825-832)Online publication date: Nov-2016
https://doi.org/10.1016/j.amepre.2016.06.013

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