The document presents Fred Stutzman's Ph.D. defense on networked information behavior during life transitions, focusing on the role of social network sites (SNS) in facilitating adaptation and support. Key research questions explore the dynamics of socio-technical networks, growth factors, and how SNS use influences adaptation to transitions such as entering college. The findings indicate that SNS plays a critical role in managing information needs and social support during such transitions, with implications for future research and system design.

1. Networked Information
Behavior in Life Transition
Fred Stutzman
Ph.D. Defense, December 8, 2010

2. Outline of the Talk
Networked Information Behavior in Life Transition
Introduction  Motivation and theoretical framework
and review  Research questions and hypotheses
Network  Factors of association in transitional networks
dynamics  Competing panel models of network growth
 Sample survey exploring relationship between SNS use
Support during
transition
and adaptation to transition
 Semi-structured interviews exploring SNS info. behavior
Conclusions and  Identification of limitations and conclusions
limitations  Future directions for research
Page  2

3. Acknowledgements
 Dr. Gary Marchionini, advisor
 Dr. Deborah Barreau, committee member
 Dr. danah boyd, committee member
 Dr. Sri Kalyanaraman, committee member
 Paul Jones, MFA, committee member
 Chelcy Boyer Stutzman, MSLS, invaluable
Page  3

4. Motivation
 Social technology as a critical aid in
my life transitions
 Transitions as a cause of
information need
 Social technology as a critical tool
in addressing transitional
information needs
 Observation of the networked
information behavior of a
transitional population
Page  4

5. Theoretical Framework
Socio-
Informational
Integration Processes
Into Trans.
Environment Development
Adaptation to
Transition of Support
Network
Management
of Stress
Access to
Social
Support
e.g. Ashforth, 2001; Cohen & Wills, 1985;
Cowan, 1991; Ebaugh, 1988; Ensel & Lin, 1991
Page  5

6. Research Theme
This research explores two overarching questions
 What factors influence the dynamics of
socio-technical networks during
transition?
 Does the use of a social network site
for information and support seeking
during transition increase adaptation?
Page  6

7. Research Questions
Four primary questions, employing three data sets
What factors are associated with the structure of
1 transitional socio-technical networks?
What factors are associated with the growth of
2 transitional socio-technical networks?
Does SNS use during transition increase adaptation to
3 transition?
How are SNS integrated into everyday life information
4 seeking during transition?
Page  7

8. Research Question 1
Factors of association in transitional networks
 What are the graph dynamics of a transitional socio-
technical network?
- e.g. Morris, 1998; Wasserman & Faust, 1994
 What common factors are associated with the production
of ties in a transitional socio-technical network?
- e.g. Blau, 1977; McPherson & Ranger-Moore, 1991; McPherson, Smith-
Lovin & Cook, 2001
 Do the strength of the associative factors change over
time?
Page  8

9. Theoretical Framework
Socio-
Informational
Integration Processes
Into Trans.
Environment Development
Adaptation to
Transition of Support
Network
Management
of Stress
Access to
Social
Support
e.g. Ashforth, 2001; Cohen & Wills, 1985;
Cowan, 1991; Ebaugh, 1988; Ensel & Lin, 1991
Page  9

10. Research Question 1
Factors of association in transitional networks
 Data set
- Facebook profiles, UNC Network
- Collected 8/30/05-12/27/05
- Facebook and IRB approval
Page  10

11. Research Question 1
Finding 1: What are the graph dynamics of a
transitional socio-technical network?
Page  11

12. Research Question 1
Finding 2: What factors are associated with the
production of ties in a transitional network?
Theoretical Foundation Analytical Approach Findings
 Preference factors  Exponential random  Preference factors are
 Political views graph modeling (ERGM) strongly predictive in early
 Compares observed transition (+).
 Academic major
network to Erdos-Renyi  Socio-Demographic
 Socio-Demographic random graph with factors are mixed. NC
factors Markov chain monte carlo residency (+) and gender
 Gender simulation (MCMC) (-) strongly predictive,
 Produces pseudo- interested in (+) is weakly
 “Interested in” predictive.
likelihood estimates of the
 NC residency probability of a tie  Configuration factors
 Configuration factors  Can be interpreted as a are mixed. Residence
 Residence hall logit coefficient, and as hall is strongly predictive
odds ratio when eb (+), rel. status weakly (+)
 Relationship status predictive.
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13. Research Question 1
Finding 2: What factors are associated with the
production of ties in a transitional network?
Gender Major
Page  13

14. Research Question 1
Finding 3: Do the strength of the associative
factors change over time?
Multiple ERGM Solution
 Preference factors are
strongly predictive in early
transition, decreasing
over the semester.
 Socio-Demographic
factors are mixed. NC
residency decreases,
gender plateaus early,
and interested in
increases.
 Configuration factors
are mixed. Residence
hall is strongly predictive,
rel. status decreases.
Page  14

15. Research Question 2
Factors associated with growth of transitional networks
 What profile elements are significantly associated with
network size, and at what magnitude
- Panel replication of Lampe, Ellison & Steinfield, 2007
- Novel panel model with dynamic predictor
 Does dorm placement exert a significant and robust
effect on growth trajectories of socio-technical networks
in transition?
- Data set is the freshman Facebook set employed in RQ 1 (in
derivative form)
- Estimated with multi-level regression analyses
Page  15

16. Theoretical Framework
Socio-
Informational
Integration Processes
Into Trans.
Environment Development
Adaptation to
Transition of Support
Network
Management
of Stress
Access to
Social
Support
e.g. Ashforth, 2001; Cohen & Wills, 1985;
Cowan, 1991; Ebaugh, 1988; Ensel & Lin, 1991
Page  16

17. Research Question 2
Marlow, 2009
Page  17

18. Research Question 2
Dependent Variable: Log of UNC Friends
Page  18

19. Research Question 2
Control variables standard between novel and multi-
level models
Control Variables
 Last Update
 Length of Membership
 Number of Groups
 Friends at External
Schools
 Gender
 Out of State Status
Page  19

20. Research Question 2
Indepdendent Variables
Lampe Replication Novel Model Multi-Level Model
 Predictors:  Predictors:  Predictors:
Referents Index Referents Index Referents Index
Interests Index Interests Index Interests Index
Contact Index Contact Index Contact Index
 Estimator: Change Index Change Index
 Arellano-Bond  Estimator:  Estimator:
with network  Arellano-Bond  Multi-level model
autoregressor with network with network
autoregressor size lagged
Page  20

21. Research Question 2
Panel Trajectories of Independent Variables
Independent Variables
 Contact Index
 Referents Index
 Interests Index
 Change Index
Interests
Music
Books
Movies
Page  21

22. Research Question 2
Findings 1 and 2: Model Results
Variable Lampe Novel Multi-Level
Lagged UNC Friends 0.689 0.644 0.624
Gender 0.0255 0.0156 0.0158
Last Update -0.000755 -0.000643 -0.000492
Membership Length 0.00117 0.000755 0.00113
Contact Index 0.00884 0.0105 -0.00141
Referents Index 0.0197 0.0110 0.0182
Interest Index 0.0383 0.0279 0.0407
Number of Groups 0.00282 0.00234
Out of State -0.00634 -0.0198
External Friends 0.00105 0.000878
Change Index 0.000444 0.000444
Constant (N) 1.181 (43,488) 1.257 (41,104) 1.311 (42,742)
Bold significant at p < .05
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23. Research Question 2
Finding 2: Predicted Trajectories
Page  23

24. Research Question 3
Does SNS use during transition increase adaptation to transition?
 Do supportive and socio-informational uses of SNS
increase experienced social support?
- Multiple regression models with robust errors
 Do supportive and socio-informational uses of SNS
increase adaptation to college?
- Multiple regression models with robust errors
 Do supportive and socio-informational uses of SNS
increase social support, leading to greater adaptation?
- Structural equation model
Page  24

25. Theoretical Framework
Socio-
Informational
Integration Processes
Into Trans.
Environment Development
Adaptation to
Transition of Support
Network
Management
of Stress
Access to
Social
Support
e.g. Ashforth, 2001; Cohen & Wills, 1985;
Cowan, 1991; Ebaugh, 1988; Ensel & Lin, 1991
Page  25

26. Research Question 3
Does SNS use during transition increase adaptation to transition?
First predictive model:
supportive and social- Simultaneous
informational SNS use evaluation with
Describe survey, and “social” structural equation
solicitation, and adaptation to college model
response
Step 1 Step 2 Step 3 Step 4 Step 5
Validation model: Second predictive
supportive and social- model: supportive and
informational SNS use social-informational
and received social SNS use and “general”
support adaptation to college
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27. Research Question 3
Survey framework
 Researcher developed original scales to
measure supportive (SNS-S) and socio-
informational (SNS-SIP) uses of SNS
Scale  Pilot study for scale quality
Development
 All members of 2009 UNC Freshman
class invited to survey
 Incentive: iPod touch, 30 gift cards
Survey Solicitation  30.57% Response (RR2), n=1,198
 Descriptive statistics: Facebook use,
privacy, activity
Analysis  Multivariate models
Page  27

28. Research Question 3
Variables Employed in Regression Analysis
Predictors Controls Outcome
 Predictors:  Individual: Gender,  Social Support:
1. Social network NC residency, stress Barrera’s Index of
site socio- (CES-D, PSS) Sosically
informational  Environmental: Ssupportive
processes (SNS- Roommate and Behaviors (ISSB)
SIP) scale hallmate quality,  Adaptation to
α = .8948 Facebook efficacy college: Baker and
 Support: Local and Siryk’s Student
2. Social network Facebook network Adaptation to
site support (SNS-S) size College Question-
scale α = .8900 naire (SACQ)
Page  28

29. Research Question 3
Finding 1: Relationship between SNS, Support, and Adaptation
 Validation Model: Socio-Informational and supportive uses
of SNS increase social support
 First Predictive Model: Supportive uses (SNS-S) of SNS
increase social adaptation to college
- Informational uses (sub-factors) of SNS-SIP, SNS-S increase social
adaptation to college
 Second Predictive Model: Supportive uses (SNS-S) of SNS
increase general adaptation to college
- Network uses (sub-factors) of SNS-SIP increase social adaptation to
college, role uses decrease social adaptation
Page  29

30. Research Question 3
Finding 2: SEM model of SNS, Support, and Adaptation
Page  30

31. Research Question 3
Finding 2: SEM model of SNS, Support, and Adaptation
RMSEA: 0.056, CFI: 0.799, TLI: 0.7990
Page  31

32. Research Question 4
How are SNS integrated into everyday life information seeking during
transition?
 Qualitative analysis of SNS use in transition
 Study outline
- Semi-structured interviews
- 15 interviews, approx one hour each
- Nine females and six males, snowball sampling
 Analysis
- Interviews transcribed verbatim, analyzed in Atlas.Ti
- Grounded analysis: Open coding, refinement, axial coding,
identification of theme; inductive and deductive analysis
Page  32

33. Theoretical Framework
Socio-
Informational
Integration Processes
Into Trans.
Environment Development
Adaptation to
Transition of Support
Network
Management
of Stress
Access to
Social
Support
e.g. Ashforth, 2001; Cohen & Wills, 1985;
Cowan, 1991; Ebaugh, 1988; Ensel & Lin, 1991
Page  33

34. Research Question 4
How are SNS integrated into everyday life information seeking during
transition?
Page  34

35. Research Question 4
Finding 1: SNS and everyday life information behavior
 Theme 1: Pre-transitional uses of Facebook
- The “Virtual Visit:” Browsing the pictures and profiles of
currently-enrolled students in order to get a realistic picture
of what campus life is like
- Informing: Student uses Facebook to address questions of
relevance to the transition
- Local cohort, organizational information, local information,
academic information, new peers
- Connection: Pre-population of the network in anticipation of
the transition
Page  35

36. Research Question 4
Finding 2: SNS and everyday life information behavior
 Theme 2: Use of Facebook for Social Adaptation
- Facebook and “Friending:” Facebook as a critical part of
freshman “friending” processes.
- Social Information: Facebook was a place to turn to find out
more about the people met during transition
- Coordinating social activities: Facebook facilitates the
coordination of the social life
- Coordinating outings
- Filtering and choosing
- Social awareness
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37. Research Question 4
Finding 3: SNS and everyday life information behavior
 Theme 3: Use of Facebook for Academic Adaptation
- Preparatory Uses: Students were commonly able to use
Facebook to address questions about academic success during
their transition
- Coordinating Supportive Action: A primary use of events was
to organize study and group sessions.
- Norms emerge that support separate academic and social uses
of Facebook
- Negative Case: Facebook and Time Management: Facebook
is widely perceived as a persistent distraction
Page  37

38. Review: Research Questions
Four primary questions, employing three data sets
What factors are associated with the structure of
1 transitional socio-technical networks?
What factors are associated with the growth of
2 transitional socio-technical networks?
Does SNS use during transition increase adaptation to
3 transition?
How are SNS integrated into everyday life information
4 seeking during transition?
Page  38

39. Limitations
Limitations of the study
- Results are not generalizable outside of the study’s population
- The quantitative analysis is associational in nature
- Match between scales and latent construct may be able to be
improved
- Model purification (SEM)
- Correspondence between virtual and real-world networks
- Primary data sets come from two separate populations
- Survey and semi-structured interviews draw on self-reported data
Page  39

40. Contributions
Contributions of the study
- Descriptive analysis of the structural dynamics of a transitional
cohort
- Update of the highly-regarded Lampe et al. study of Facebook
network growth with panel data
- Development of two new constructs to measure specific uses of
social network sites during transition
- Identification of the relationship between SNS use, social support,
and adaptation to transition
- Identification of important everyday uses of SNS during transition
(semi-structured interviews)
Page  40

41. Implications and Future Directions
Next steps
 Implications
- “Situational Relevance” of SNS in transition – the SNS is a place where we
can answer information needs in times of life change.
- Versatile – addresses a range of needs
- Network structure of participation creates an information rich space
- Identity sharing promotes positive participation
- Facebook, in particular, has positive norms of disclosure that facilitate transmission of
important information
- Sites address “social motives” – we get something when we participate
- SNS has flexible infrastructure supporting ad-hoc collaboration
- Systems should identify and adapt to transitions
- Characteristics of networks make them identifiable
- Sites could adapt to information needs during transitional period
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42. Implications and Future Directions
Next steps
 Implications
- Facilitating interaction during transition
- For sites to be useful, we must find each other in transition
- Organizations can foster social practice to overcome technological limitation
- The negotiation of shared identifiers in an evolving space will continue to pose
challenges for those wishing to take advantage of SNS during transition
 Future Research
- Explore new transitions: organizational, military-to-civilian life
- Design systems that intelligently adapt to transition
- Design systems and practice that encourage ad-hoc collaboration to address
information needs, particularly those of repressed individuals within
organizational hierarchy (whistleblowers, organizers)
Page  42

43. Thank you!
fred@fredstutzman.com
http://fredstutzman.com
http://twitter.com/fstutzman
Page  43

44. References
 Ashforth, B. E. (2001). Role Transitions in Organizational Life: An Identity-Based
Perspective. Mahwah, NJ: Lawrence Erlbaum Associates.
 Baker, R. W. and Siryk, B. (1989). Student Adaptation to College Questionnaire. Los
Angeles, CA: Western Psychological Services.
 Cohen, S. and Wills, T. A. (1985). Stress, Social Support, and the Buffering Hypothesis.
Psychological Bulletin, 98(2), 310--357.
 Cowan, P. A. and Hetherington, M. (1991). Family Transitions. New York: Lawrence
Erlbaum Associates.
 Ebaugh, H. R. F. (1988). Becoming an Ex: The Process of Role Exit. Chicago, Illinois:
University of Chicago Press.
 Lampe, C., Ellison, N. B., and Steinfield, C. (2007). A Familiar Face (Book): Profile
Elements as Signals in an Online Social Network. In CHI '07: Proceedings of the SIGCHI
Conference on Human Factors in Computing Systems, New York, NY, USA, 2007 (pp.
435--444). ACM.
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