Presentation at the International Conference of Human-Computer Interaction (HCII'20). Remote presentation, July 21, 2020.

1. Enriching Social Media Personas with
Personality Traits: A Deep Learning
Approach Using the Big Five Classes*
Joni Salminen
Rohan Rao
Soon-gyo Jung
Shammur Chowdhury
Bernard J. Jansen
Qatar Computing Research Institute, Hamad Bin Khalifa University
Indian Institute of Technology Madras
*Download the paper:
http://www.bernardjjansen.com/uploads/2/4/1/8/24188166/salminen2020_chapter_enriching
socialmediapersonaswi.pdf

2. QCRI

3. EDUCATION
CITY
STADIUM

4. CRICKET
BOWIE

5. Personas…
• …are fictitious people that describe user or
customer segments of a software system, product,
or service.
• …are widely used in many fields, including e.g.
software development, design, marketing, health
informatics, and so on.
• …simplify numbers about users into an easy-to-
understand representation: another human being.
• …help make user-centric decisions while keeping
the end-user in mind.

6. ”Personas give faces to data.”
A lot of numbers …
Austin, a 35-year-old guy
who is single and uses iOS.
vs.

7. Personas are now data-driven!
• Data-driven personas are created using
algorithms and online user data.
• Social media personas are a subset of
data-driven personas.
• …quick to create, based on quantitative
data, easy to update when user
behavior changes.
Literature:
• McGinn, J. (Jen), & Kotamraju, N. (2008). Data-
driven persona development. Proceeding of
the Twenty-Sixth Annual CHI Conference on
Human Factors in Computing Systems - CHI
’08, 1521.
https://doi.org/10.1145/1357054.1357292
• Salminen, J., Guan, K., Jung, S.-G., Chowdhury,
S. A., & Jansen, B. J. (2020). A Literature
Review of Quantitative Persona Creation. CHI
’20: Proceedings of the 2020 CHI Conference
on Human Factors in Computing Systems, 1–
14. https://doi.org/10.1145/3313831.3376502

8. Automatic Persona
Generation
https://persona.qcri.org

9. Personas are data-driven, but…
• …currently miss automatically inferred personality traits
• Rounded persona principle [1] = personas should have all
the information that decision makers using them need.
• Personality is information that has been missing from
data-driven personas but could be useful for decision
makers → linked with things like shopping behavior,
voting behavior, search behavior, problem solving…
[1] Nielsen, L. (2019). Personas—
User Focused Design (2nd ed.
2019 edition). Springer.

10. The research problem
How to infer personas’ personality traits
automatically from user-generated content in social
media?

11. Combine DDPs + APD
• DDP = Data-Driven Persona
• APD = Automatic Personality Detection
• Persona quotes + APD = personality traits for personas
• (Note that data-driven persona quotes are persona-specific.)
• …marriage of technology!

12. Datasets
• YouTube (YT): 404 vlog transcripts (240,580 words)
• Facebook: 9,880 status updates (143,639 words)
• Essays: 2,467 stream-of-conciousness essays (1,609,042)
• PERSONAS: 206K video views from 13K videos published between
January 1, 2016 and September 30, 2018 on a YT channel of Al Jazeera
Media Network (AJ+ ). For the data collection, we used the YT Analytics
Application Programming Interface (API ) with the channel owner’s
permission.

13. Personality traits [2]
• Openness: Artistic, curious, imaginative, curious, intelligent, and
imaginative. Open individuals tend to be artistic and have
sophisticated taste. They appreciate diverse views, ideas, and
experiences.
• Conscientiousness: Efficient, organized, responsible, organized, and
persevering. Conscientious individuals tend to be reliable and
focused on achieving, working hard, and planning for the future.
• Extroversion: Energetic, active, assertive, outgoing, amicable,
assertive. These individuals are friendly and energetic, drawing
inspiration from social situations.
• Agreeableness: Compassionate, cooperative, cooperative, helpful,
nurturing. Individuals that score high in agreeableness are
peacekeepers. They are generally optimistic and trusting of others.
• Neuroticism: Anxious, tense, self-pitying, anxious, insecure,
sensitive. Neurotics are moody, tense, and easily tipped into
experiencing negative emotions.
• [2] Norman, W.T.: Toward an
adequate taxonomy of personality
attributes: Replicated fac-tor
structure in peer nomination
personality ratings. The Journal of
Abnormal and Social Psychology.
66, 574 (1963)
• Google Scholar: 341,000 results
for [“big five” + personality]

14. Algorithms
• LSTM1 (bidirectional) + CNN2
• Features: Word2Vec3 (300D)
• Max Pooling, Spatial Dropout, Dropout and
Batch Normalization
• Adam optimizer, 10 epochs
• (The neural network uses 80-10-10 split,
10-fold cross-validation)
Notes:
1Long Short-Term Memory
2Convolutional Neural Network
3Mikolov, T., Sutskever, I., Chen, K., Corrado,
G. S., & Dean, J. (2013). Distributed
Representations of Words and Phrases and
their Compositionality. In Advances in
Neural Information Processing Systems 26
(pp. 3111–3119).

15. Experiment design
1. Generate 15 personas from Al Jazeera data
2. Aggregate each personas’ YouTube comments
3. Predict the “Big Five” personality traits of each persona
from the comments pertaining to that persona (each trait
separately)
4. Evaluate (F1 score)

16. Results (1/2)
Baseline: Majumder, N., Poria, S., Gelbukh, A., Cambria, E.:
Deep Learning-Based Document Modeling for Personality
Detection from Text. IEEE Intelligent Systems. 32, 74–79
(2017). https://doi.org/10.1109/MIS.2017.23

17. Results (2/2)

18. Design
implications

19. Challenges
• Conceptual: what is personality? How to operationalize
personality traits for social media?
• Data: does one tweet predict your personality?
• Theoretical: group personality vs. individual personality
• UI: how should persona personality traits be shown to
persona users?

20. Thank you!
Salminen, J., Rao, R. G., Jung, S., Chowdhury, S. A., & Jansen, B. J. (2020,
July 19). Enriching Social Media Personas with Personality Traits: A
Deep Learning Approach Using the Big Five Framework. In the
Proceedings of the 22nd International Conference on Human-
Computer Interaction (HCII’20).
Email: jsalminen@hbku.edu.qa