Review of "Tastes, ties, and time: A new social network dataset using Facebook.com"

Brief report about the paper titled "Tastes, ties, and time: A new social network dataset using Facebook.com"

1. Tastes, ties, and time: A new social network
dataset using Facebook.com
Lewis, K., Kaufman, J., Gonzalez, M., Wimmer, A. & Christakis, N. Tastes, ties, and time:
A new social network dataset using facebook.com. Social Networks In Press, Accepted
Manuscript (2008).
URL http://dx.doi.org/10.1016/j.socnet.2008.07.002

2. Paper overview
Introduction of a new public datased retrieved
from a popular SNS
Features of this dataset
Descriptive findings from this dataset (actually
early findings...)

3. Background
Research dataset retrieved from Facebook.com
Why Facebook.com?
Several articles published on Facebook, accepted as
a “standard”
Has profile creation and network articulation as
primary community tasks (Lampe et al., 2007)
Facebook communities generally correspond to
existing offline network membership (Lampe et al.,
2007)
Provides users with standardized profile templates

4. State of the art
Several articles published on Facebook, for
example:
Identity Management: Multiple Presentations of Self in
Facebook (DiMicco et al., 2007)
A Familiar Face(book): Profile Elements as Signals in
an Online Social Network (Lampe et al., 2007)

5. State of the art
Past research has tended to draw upon only a very small
portion of the wealth of data available on Facebook.
Most focused only on profile data, ignoring network ties
between users: no study made use of data on user tastes

6. Data collection
Using an official roster provided by a college, profile and network
data provided by one cohort of college students were downloaded.
College provided additional data on those students: link between
online profile and college housing record.
Five defining features of the dataset:
Natural research instrument
Complete network data
Longitudinal data (analysis replied for 4 years)
Data on multiple social relationships (three measures of
relationships)
Cultural data (Facebook profiles contains open-ended spaces for
respondents → tastes!)

7. Three measures of relationships
Network size (degree centrality) histograms for Facebook friends, picture friends, and housing
groupmates. Note: students with no photo albums (zero outgoing ties)
are omitted from outgoing picture friend histogram.

8. Dataset
All explanatory variables are inferred or directly
drawn from students' Facebook profiles
(e.g. Sex, Home Town, …)
Race/ethnicity and socioeconomic status (SES)
retrieved with more elaborate procedures (photo
albums, socioeconomic national data, ..)

9. Population demographics
Diversity of population
allows to make
comparison across
subgroups

10. Methodology
Network properties as size, density and
betweenness centrality calculated using UCINET
Network ethno-racial diversity calculated using
IQV (index of qualitative variation). It measures
the heterogeneity of ego’s network independent of
the race/ethnicity of ego

11. Methods
Used OLS regression (multivariables regression)
to see how gender, race/ethnicity, SES, and
online activity are associated with our network
variables of interest

12. Culture
Compiled three spreadsheets of data (on for each
kind of taste) with the data retrieved from
students' Facebook profile linking the student to
their cultural preferences
Calculated the proportion of taste overlap for
every possible dyads

13. The shape of cultural proclivities
OLS regression coefficients for
shared tastes in movies,
music and books
Note: p-values determined by
MRQAP. All coefficients
reported in percentages (%).
*p < .05; **p < .01; ***p≤.001.

14. Conclusion
Introduced a new public database available here:
http://dvn.iq.harvard.edu/dvn/dv/t3
Starting point to future social network research
involving cultural preferences as well as social,
socioeconomic and demographic aspect.