Interacting with Digital Individuals:Opportunities and Risks of Discovering Personality Traits from Social Media

ModeratorsMichelle Zhou, Jeffrey Nichols

PanelistsVictoria Bellotti, Tom Dignan, Jennifer Golbeck, Jeff Hancock

Michelle Zhou Jeffrey NicholsIBM Research – Almaden, IBM Watson Group

Outline

• Introduction (30 min)• Digital individuals from Social Media (live demo)

• Intro presentations from each Panelist

• Q&A with audience (45 min)

• Summary (5 min)

Analytics of Aggregates

Monitoring and Reporting

Analytics of Individuals

Sentiment

Listening Engagement Workflow

Measurement

Publishing

Net Promoter

Network Topology

Mas

s

Indivi

dual

Intrinsic Traits

What are people saying?

How do people feel about my brand?

Who is this individual? What motivates her? What is her taste and style?

Next generation

Earlystages

State of the art

Social Genome

• Demographics• Birthday• Age• Home Location• Political Affiliation• Religion• Etc.

• Intrinsic Traits• Personality (Big 5)• Basic Human Values

(Motivations)• Fundamental Needs

(Buying behaviors)• Emotional State• Etc.

Information That Can Be Extracted

From Social Media

DEMO

IBM System U

Methodology: Personality Analytics

“I love food, .., with … together we … in… very…happy.”

Word category: Inclusive Agreeableness

[Tausczik and Pennebaker ‘10, Yarkoni ‘10]

Automatically compute one’s personality traits

Make hyper-personalized recommendations based on derived traits[Ford ‘05, O’Brien ‘96, Neuman ‘99, Gosling ‘03, Wholan ‘06]

Do it for hundreds of millions of individuals

Opportunities Individualization at Scale

“Welcome to our store, would you like to take a personality test?”

Privacy invasion

Veracity of social media

Analytics imperfections

RisksIndividualization misfire

“Your tweets tell us that you appear to have multiple

personalities”

“We do not hire vulnerable people like you”

ProfessorCommunication, Information ScienceCornell University

Areas of Interest• Computer-mediated

communication• Language and technology• Deception and its detection • Figurative language

Jeff Hancock

ProfessorCollege of Information StudiesUniversity of Maryland

Areas of Interest• Trust modeling• Personality and political

preference from social media• Usable Security

Jennifer Golbeck

Vice President, Head of Research Reputation.com

Areas of Interest• Reputation scoring• Big data analytics and

platforms for real-world systems

Tom Dignan

Reputation.com is: The pioneering leader in the online reputation management &

digital privacy space We monitor the online presence of individuals and businesses

What shows up in your search results What people say about you on Facebook, Twitter, and other

social media sites What PPI do you have exposed What photos or videos are tagged with your name What public records are exposed

We assess and manage your digital footprint Is the content about you negative or positive (sentiment

analysis) How much personal information do you have exposed Where is your online presence lacking

What Does Reputation.com Do?

The Driving Factors for Reputation.com’s Business:

As more and more of people’s lives are conducted online, there is a growing desire to enjoy the benefits of interacting on the internet whilst maintaining control of one’s online profile, presence and personal data.

Philosophy: people and businesses have a right to control, protect their online reputations and privacy.

Online reputation will only grow in importance: ample research demonstrates that consumers are actively searching online and trusting what they find – and businesses are materially impacted by social media/review feedback.

What is Driving Reputation.com’s Business?

Research FellowPARC

Areas of Interest• Ethnography• Task and activity management• Context-aware computing• Sharing economy and

collaborative consumption

Victoria Bellotti

Context-Aware Computing: Activity Spotting

Time

No. of crowdsourced

activity features

spotted per interval

Inferential threshold Writing a paper

Not writing a paper

Ben Sutherland - Flickr

Rethinking the TimeBanking Metaphor: Do humans need to be paid to be nice?

Policies and Practice: Doing the Right ThingWednesday 2:00-3:30pm Room: 801BTalk is scheduled to start at 3:10 pm

Q&A

• How to interpret or measure the accuracy of personality traits derived from social media?

• What factors (e.g., data sources and analytics methods) may affect accuracy?

• What could the derived personality traits be used for individuals and businesses?

• Who would benefit the most? • What are the risks of using such technologies, especially from an

individual perspective? • Who is at risk?• How can we protect ourselves?• …

Summary

• To be filled in during the panel

Validation

How good are our results compared to standard psychometric studies?

How well can our results be used to predict or influence one’s behavior?

Yarkoni ’10, Adali ‘12, Chen ‘14, Gou ’14 …

Mahmud ‘13, Lee ‘14

Results

• RV-Coefficient correlation analysis of each type of trait

• Over 80% of population, their correlation is statistically significant (80.8%, 98.21%, and 86.6% for Big 5 personality, basic values and needs)

[Gou et al. CHI 2014]

References• Chen, J., Hsieh, G., Mahmud, J., and Nichols, J. Understanding individuals personal values from social media

word use. In ACM Proc. CSCW ’2014. • Ford, J. K. Brands Laid Bare. John Wiley & Sons, 2005. • Gou, L., Zhou, M.X., and Yang, H. KnowMe and ShareMe: Understanding automatically discovered personality

traits from social media and user sharing preferences. In ACM Proc. CHI 2014.• Lee, K., Mahmud, J., Chen, J., Zhou, M.X., and Nichols, J. Who will retweet this? Automatically identifying and

engaging strangers on Twitter to spread information. In ACM Proc. IUI ‘2014.• Luo, L., Wang, F., Zhou, M.X., Pan, X., and Chen, H. Who’s got answers? Growing the pool of answerers in a

smart enterprise Social Q&A system. In ACM Proc. IUI ‘2014. • Mahmud, J., Zhou, M.X., Megiddo, N., Nichols, J., and Drews, C. Recommending Targeted Strangers from Whom

to Solicit Information in Twitter. In ACM Proc. IUI ‘2013. • Schwartz, S. H. Basic human values: Theory, measurement, and applications. Revue francaise de sociologie,

2006. • Tausczik, Y. R., and Pennebaker, J. W. The psychological meaning of words: LIWC and computerized text analysis

methods. Journal of Language and Social Psychology 29, 1 (2010), 24–54.• Yang, H., and Li, Y. Identifying user needs from social media. IBM Tech. Report (2013).• Yarkoni, T. Personality in 100,000 words: A large-scale analysis of personality and word use among bloggers. J.

research in personality 44, 3 (2010), 363–373.