The Name-Letter Effect states that people have a preference for brands, places, and even jobs that start with the same letter as their own first name. So Sam might like Snickers and live in Seattle. We use social network data from Twitter and Google+ to replicate this effect in a new environment. We find limited to no support for the Name-Letter Effect on social networks. We do, however, find a very robust Same-Name Effect where, say, Michaels would be more likely to link to other Michaels than Johns. This effect persists when accounting for gender, nationality, race, and age. The fundamentals behind these effects have implications beyond psychology as understanding how a positive self-image is transferred to other entities is important in domains ranging from studying homophily to personalized advertising and to link formation in social networks.

1. The Social Name-Letter Effect
on Online Social Networks
Farshad Kooti Ingmar Weber
Gabriel Magno
This work was done while the first two authors were interns at QCRI

2. The Name-Letter Effect
(NLE)

3. The Name-Letter Effect
Sarah
Sam
Starbucks
San Francisco
Sales

4. Where the SNE Has Been
Observed
● Nuttin (1985): letter-picking
– across languages [Hoorens 1990]
● Observed in decision making situations
– Cities and jobs [Pelham 2002]
– Brands [Brendl 2005]
– Donations [Bekkers 2010]
– Marriage [Jones 2004, Simonsohn 2011]
– Favorite foods & animals [Hodson 2005]
● Challenging the existence of NLE
– Biases
– Methodology
N
A
S
Arthur

5. Motivation
● Widely cited effect in psychology,
but has been questioned by some
researchers
● Understanding factors affecting
social link formation is important
● Successful market example: "share
a coke" campaign
– People love their name!

6. NLE on
Online Social Networks

7. Datasets
● Twitter: 2009
– 52 Mi users
– 1.9 Bi edges
● Google+: 2012
– 61 Mi users
– 1 Bi edges

8. Methodology
Brand X* Brand Y*
Users X* A
Users Y*
C
B
D
( A+C)∗(A+B)
A+B+C+D
A → # users X* following brand X*
B → # users X* following brand Y*
C → # users Y* following brand X*
D → # users Y* following brand Y*
Expected
value for A
Observed value > Expected value → NLE

9. Brand Preference
Statistically significant NLE

10. Other NLE analysis
● Social Link: names with same 1st letter
– Statistically significant, but negative NLE
● Location: 10 US cities, 7 letters, 21 pairs
– 8 pairs, 6 positive
● Occupation: 5 jobs, 5 letters, 10 pairs
– 1 pair, negative
● Hobbies: 8 sports, 7 letters, 21 pairs
– 4 pairs, 1 positive
James John
Overall, no consistent Name-Letter Effect

11. The Same-Name
Effect on OSNs

12. Name Preference
● Correcting for country (US) and gender
● Top 5 popular names
● Similar results for Google+ and females
Users significantly preferred to follow
other users with the same name

13. Ethnicities
● Last name as proxy for race
● 5 races (US), top 500 “exclusive” last names
Strong and consistent SNE for all the 5 races

14. Other SNE analysis
● Language: Brazil, Egypt, Germany
– Effect sizes between 6% and 101%
● Social Tie Strength: common friends
– People are more affected by SNE when they
are establishing a weak link
● Number of friends:
– Users with fewer friends are more likely to
follow other users with the same name

15. Conclusion

16. Concluding Remarks
● Investigated the existence of the NLE in the context
of Twitter and Google+
– Findings question, at least, the generality of the NLE
● Investigated the existence of SNE
– Robust effect, even when accounting for gender, age,
race, and location

17. Remember that a
person's name is, to that
person, the sweetest and
most important sound in
any language.
Dale Carnegie, in the book
“How to Win Friends and
Influence People”

18. Thank You!
http://www.dcc.ufmg.br/~magno
@GabrielMagno

19. Backup Slides

20. Social Link Preference
Statistically significant, but negative NLE