1. Simulating Virtual Behaviour A Facebook “Like” Questionnaire
Christine L. Cook, Mphil (PhD Candidate)
Supervised by Dr. Aleksandr Kogan (Spectre)

2. Facebook Research – A Brief History
Social networking research was spearheaded by Dr. Jen Golbeck.
Predicting Personality by analysing “tweets” (Twitter; )
Facebook “likes” were further explored by Kosinski, Stillwell, & Graepel (2012).
“Likes” are binomial (yes or no/indifferent), public information.
Reduced via principal component analysis (PCA) to 100 dimensions.
Correlations with actual data range from 0.17 (satisfaction with life) to 0.85 (age).
This technique was refined by Kogan & Chancellor.
Likes are entered into a co-occurrence matrix, eliminating the sparseness of data.
Instead of 50,000+ participants, models can be trained on samples as small as 1000.

3. Limits of the Research People need Facebook accounts!
People need to be willing to authorize access to their accounts.
Recent unethical research (The Guardian, 2014)
General unease with “big brother” (i.e. NSA, CCTV …)
Fear of additional information being downloaded.
Testing requires an internet connection.

4. The Current Study
GOAL: Create a paper-pencil alternative to Facebook account access.
Kogan & Chancellor’s models were trained on an American population, therefore all participants in this study must also be American.
Participants were recruited via Tellwut, a Toronto-based survey panel.

5. Making the Facebook Like Simulator (FLS)
Walmart
Amazon.com
Ebay.com
T-Pain
1.000
0.874
0.863
0.412
0.973
0.381
0.566
The top 500 Facebook “likes” were found in 2014 by Kogan & Chancellor.
These were entered into a correlation matrix.
Any item-pairs that correlated at 0.90 or higher were flagged; the highest-ranked item was kept, the other discarded.

7. Methodology Participants Procedure Participants Procedure
Study 1
Study 2
Participants
1247 completed the survey
1000 authorized the app
Procedure
Consent Form/Information Sheet
Authorization of Facebook Harvester App
Completion of FLS
Redirect to Tellwut for reward
Participants
1019 completed the survey
842 authorized the app
Procedure
Same as Study 1, + BFI
-60 participants (no response variance)
-Items 2, 12, 21, 23, 24, 26-29, 31, 32, , and 44 (sub-scale reliability)

8. Machine Learning Algorithms
Based on FLS
Likes used
Self Report Data
Demographic Q’s
Big Five Inventory (BFI)
Based on FB
All possible likes used
Testing Sample: 8364 participants from Kogan & Chancellor’s original research.

9. Study 1 Results
Age
Gender

10. Study 2 Results
Openness
Conscientiousness

11. Study 2 Results
Extraversion
Agreeableness

12. Study 2 Results
Neuroticism

13. Final Results One scale of 60 items.
Ability to predict personality, age, and gender retroactively.
More accuracy than using harvested FB likes.

14. The Next Steps Validate completed FLS on multiple existing scales
Use the FLS in other United States-based studies as a personality measure
Laboratory studies with small n’s
Large-scale surveys without a Facebook component
Perform Kogan & Chancellor’s initial work in other countries
Hong Kong
Russia UK
Create FLS versions appropriate to these other cultures

15. Thank you for your attention.

16. Detailed Training Sample Information
Study 1
Study 2
Age range: (M = 47.33, SD = 17.83)
79.48% Female, 20.52% Male
Age range: (M = 48.70, SD = 17.55)
79.01% Female, 20.99% Male

17. Detailed Test Sample Information
Age range: (M = 29.99, SD = 12.31)
53.20% Female, 46.80% Male
Racial data was not available for this test set.
32 participants claimed to be over 100 years old and were thus eliminated as “missing data”.
With the exception of the FLS, this sample had completed all the same questionnaires as the training sample.
The same test sample was used in both study 1 and study 2.

18. Data Processing (FLS and Facebook)
Raw Data
Sparse
1’s and 0’s
Co-occurrence Matrix
Person to Group
Dense to Rich
Comparable Scores
100 dimensions

19. Study 1 Results – FLS to Facebook
Age
Gender

20. Study 2 Results Neuroticism FLS to Facebook? Openness -> 40 Likes
Conscientiousness -> 120 Likes
Extraversion -> 90 Likes
Agreeableness -> 100 Likes
Neuroticism -> 80 Likes