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KnowMe and ShareMe: understanding automatically discovered personality traits from social media and user sharing preferences

Authors:

Michelle X. Zhou,

Huahai YangAuthors Info & Claims

CHI '14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 955 - 964

https://doi.org/10.1145/2556288.2557398

Published: 26 April 2014 Publication History

Abstract

There is much recent work on using the digital footprints left by people on social media to predict personal traits and gain a deeper understanding of individuals. Due to the veracity of social media, imperfections in prediction algorithms, and the sensitive nature of one's personal traits, much research is still needed to better understand the effectiveness of this line of work, including users' preferences of sharing their computationally derived traits. In this paper, we report a two- part study involving 256 participants, which (1) examines the feasibility and effectiveness of automatically deriving three types of personality traits from Twitter, including Big 5 personality, basic human values, and fundamental needs, and (2) investigates users' opinions of using and sharing these traits. Our findings show there is a potential feasibility of automatically deriving one's personality traits from social media with various factors impacting the accuracy of models. The results also indicate over 61.5% users are willing to share their derived traits in the workplace and that a number of factors significantly influence their sharing preferences. Since our findings demonstrate the feasibility of automatically inferring a user's personal traits from social media, we discuss their implications for designing a new generation of privacy-preserving, hyper-personalized systems.

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Cited By

Kumar PZimmer MVitak J(2024)A Roadmap for Applying the Contextual Integrity Framework in Qualitative Privacy ResearchProceedings of the ACM on Human-Computer Interaction10.1145/36537108:CSCW1(1-29)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3653710
Shen DZhu HXiao KZhang XXiong H(2023)Exploiting Connections among Personality, Job Position, and Work Behavior: Evidence from Joint Bayesian LearningACM Transactions on Management Information Systems10.1145/360787514:3(1-20)Online publication date: 12-Sep-2023
https://dl.acm.org/doi/10.1145/3607875
Anuyah OBadillo-Urquiola KMetoyer R(2023)Characterizing the Technology Needs of Vulnerable Populations for Participation in Research and Design by Adopting Maslow’s Hierarchy of NeedsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581221(1-20)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581221
Show More Cited By

Index Terms

KnowMe and ShareMe: understanding automatically discovered personality traits from social media and user sharing preferences
1. Human-centered computing
  1. Human computer interaction (HCI)
2. Social and professional topics
  1. Computing / technology policy

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cover image ACM Conferences

CHI '14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

April 2014

4206 pages

ISBN:9781450324731

DOI:10.1145/2556288

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 ACM.

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Published: 26 April 2014

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April 26 - May 1, 2014

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CHI '14 Paper Acceptance Rate 465 of 2,043 submissions, 23%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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Cited By

Kumar PZimmer MVitak J(2024)A Roadmap for Applying the Contextual Integrity Framework in Qualitative Privacy ResearchProceedings of the ACM on Human-Computer Interaction10.1145/36537108:CSCW1(1-29)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3653710
Shen DZhu HXiao KZhang XXiong H(2023)Exploiting Connections among Personality, Job Position, and Work Behavior: Evidence from Joint Bayesian LearningACM Transactions on Management Information Systems10.1145/360787514:3(1-20)Online publication date: 12-Sep-2023
https://dl.acm.org/doi/10.1145/3607875
Anuyah OBadillo-Urquiola KMetoyer R(2023)Characterizing the Technology Needs of Vulnerable Populations for Participation in Research and Design by Adopting Maslow’s Hierarchy of NeedsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581221(1-20)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581221
Bozarth LQuercia DCapra LŠćepanović S(2023)The role of the big geographic sort in online news circulation among U.S. Reddit usersScientific Reports10.1038/s41598-023-33247-313:1Online publication date: 25-Apr-2023
https://doi.org/10.1038/s41598-023-33247-3
Frauenstein EFlowerday SMishi SWarkentin M(2023)Unraveling the behavioral influence of social media on phishing susceptibility: A Personality-Habit-Information Processing modelInformation & Management10.1016/j.im.2023.10385860:7(103858)Online publication date: Nov-2023
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Lee KSong S(2022)Developing insights from the collective voice of target users in TwitterJournal of Big Data10.1186/s40537-022-00611-59:1Online publication date: 2-Jun-2022
https://doi.org/10.1186/s40537-022-00611-5
Ramokapane KSuch JRashid A(2022)What Users Want From Cloud Deletion and the Information They Need: A Participatory Action StudyACM Transactions on Privacy and Security10.1145/354657826:1(1-34)Online publication date: 7-Nov-2022
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Zhao YMiao DCai Z(2022)Reading Personality Preferences From Motion Patterns in Computer Mouse OperationsIEEE Transactions on Affective Computing10.1109/TAFFC.2020.302329613:3(1619-1636)Online publication date: 1-Jul-2022
https://doi.org/10.1109/TAFFC.2020.3023296
Ye QCao YChen YLi CLi X(2022)Deep Learning-Based User Privacy Settings Recommendation in Online Social Networks2022 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN55064.2022.9892734(1-9)Online publication date: 18-Jul-2022
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Shibuya YHamm ACerratto Pargman T(2022)Mapping HCI research methods for studying social media interactionComputers in Human Behavior10.1016/j.chb.2021.107131129:COnline publication date: 1-Apr-2022
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