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This study explores the supportive and informational uses of social network sites that facilitate adaptation to transition. This study focuses on the transition to college, a major life event requiring integration into new settings, the negotiation of informational challenges, and the mastery of new roles and identities. Adaptation to transition is a complex process contingent upon the management of stress associated with transition and general integration into the transitional environment. Social network sites represent a connective infrastructure within personal networks. Because social network sites are inherently connective, they afford a location for provision and receipt of social support during transition, and a site for the acquisition of information necessary for integration into the transitional environment. Drawing on data collected directly from a social network site that describes the networked activity of a freshman class over the course of their first semester at college, from a sample survey of freshmen with 1,198 respondents, and from 15 semi-structured interviews, this research has two primary components. In the first component of analysis, I explore the structure and dynamics of socio-technical networks during transition. Using exponential random graph modeling, I identify the role and magnitude of preference, socio-demographic, and configuration factors in structuring socio-technical networks during transition. I then use an econometric framework to demonstrate that certain types of information sharing and profile change are associated with socio-technical network growth. In the second component of analysis, I explore uses of social network sites that facilitate adaptation to transition. Using multiple regression and structural equation modeling, I demonstrate that supportive and social-informational uses of social network sites in transition exert a direct and mediated positive effect on overall adaptation. I then draw on interviews to explore supportive and informational uses of the social network site during transition, finding that social network sites are useful in pre-transition preparation, for social adaptation, and for academic support throughout the transition. Upon evaluation, I demonstrate that a social network site is a useful place to turn for the social and informational support that facilitates adaptation to transition.
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Networked Information Behavior in Life Transition Fred Stutzman Ph.D. Defense, December 8, 2010
Outline of the Talk
Page 2
Introduction and review
Motivation and theoretical framework Research questions and hypotheses
Network dynamics
Factors of association in transitional networks Competing panel models of network growth
Support during transition
Sample survey exploring relationship between SNS use and adaptation to transition
Semi-structured interviews exploring SNS info. behavior
Conclusions and limitations
Identification of limitations and conclusions Future directions for research
Networked Information Behavior in Life Transition
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
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
Theoretical Framework
Page 5
Adaptation to Transition
Integration Into Trans.
Environment
Management of Stress
Socio- Informational Processes
Development of Support Network
Access to Social
Support e.g. Ashforth, 2001; Cohen & Wills, 1985; Cowan, 1991; Ebaugh, 1988; Ensel & Lin, 1991
Research Theme
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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?
This research explores two overarching questions
Research Questions
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What factors are associated with the structure of transitional socio-technical networks?
What factors are associated with the growth of transitional socio-technical networks?
Does SNS use during transition increase adaptation to transition?
How are SNS integrated into everyday life information seeking during transition?
1
2
3
4
Four primary questions, employing three data sets
Research Question 1
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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?
Factors of association in transitional networks
Theoretical Framework
Page 9
Adaptation to Transition
Integration Into Trans.
Environment
Management of Stress
Socio- Informational Processes
Development of Support Network
Access to Social
Support e.g. Ashforth, 2001; Cohen & Wills, 1985; Cowan, 1991; Ebaugh, 1988; Ensel & Lin, 1991
Research Question 1
Page 10
Data set - Facebook profiles, UNC Network - Collected 8/30/05-12/27/05 - Facebook and IRB approval
Factors of association in transitional networks
Research Question 1
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Finding 1: What are the graph dynamics of a transitional socio-technical network?
Research Question 1
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Finding 2: What factors are associated with the production of ties in a transitional network?
Preference factors Political views
Academic major
Socio-Demographic factors
Gender
“Interested in”
NC residency
Configuration factors Residence hall Relationship status
Theoretical Foundation
Exponential random graph modeling (ERGM)
Compares observed network to Erdos-Renyi random graph with Markov chain monte carlo simulation (MCMC)
Produces pseudo-likelihood estimates of the probability of a tie
Can be interpreted as a logit coefficient, and as odds ratio when eb
Analytical Approach
Preference factors are strongly predictive in early transition (+).
Socio-Demographic factors are mixed. NC residency (+) and gender (-) strongly predictive, interested in (+) is weakly predictive.
Configuration factors are mixed. Residence hall is strongly predictive (+), rel. status weakly (+) predictive.
Findings
Research Question 1
Page 13
Finding 2: What factors are associated with the production of ties in a transitional network?
Gender Major
Research Question 1
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Finding 3: Do the strength of the associative factors change over time?
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.
Multiple ERGM Solution
Research Question 2
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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
Factors associated with growth of transitional networks
Theoretical Framework
Page 16
Adaptation to Transition
Integration Into Trans.
Environment
Management of Stress
Socio- Informational Processes
Development of Support Network
Access to Social
Support e.g. Ashforth, 2001; Cohen & Wills, 1985; Cowan, 1991; Ebaugh, 1988; Ensel & Lin, 1991
Research Question 2
Page 17
Marlow, 2009
Research Question 2
Page 18
Dependent Variable: Log of UNC Friends
Research Question 2
Page 19
Control variables standard between novel and multi-level models
Last Update Length of Membership Number of Groups Friends at External
Schools Gender Out of State Status
Control Variables
Research Question 2
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Indepdendent Variables
Predictors: Referents Index
Interests Index Contact Index
Estimator: Arellano-Bond
with network autoregressor
Lampe Replication
Predictors: Referents Index
Interests Index Contact Index
Change Index Estimator:
Arellano-Bond with network autoregressor
Novel Model
Predictors: Referents Index
Interests Index Contact Index
Change Index Estimator:
Multi-level model with network size lagged
Multi-Level Model
Research Question 2
Page 21
Panel Trajectories of Independent Variables
Contact Index Referents Index Interests Index Change Index
Interests Music Books Movies
Independent Variables
Research Question 2
Page 22
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
Research Question 2
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Finding 2: Predicted Trajectories
Research Question 3
Page 24
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
Does SNS use during transition increase adaptation to transition?
Theoretical Framework
Page 25
Adaptation to Transition
Integration Into Trans.
Environment
Management of Stress
Socio- Informational Processes
Development of Support Network
Access to Social
Support e.g. Ashforth, 2001; Cohen & Wills, 1985; Cowan, 1991; Ebaugh, 1988; Ensel & Lin, 1991
Research Question 3
Page 26
Does SNS use during transition increase adaptation to transition?
Step 1 Step 2 Step 3 Step 4 Step 5
First predictive model: supportive and social-informational SNS use and “social” adaptation to college
Simultaneous evaluation with
structural equation model
Validation model: supportive and social-informational SNS use and received social support
Second predictive model: supportive and social-informational SNS use and “general” adaptation to college
Describe survey, solicitation, and response
Research Question 3
Page 27
Survey framework
Researcher developed original scales to measure supportive (SNS-S) and socio-informational (SNS-SIP) uses of SNS
Pilot study for scale quality Scale Development
Survey Solicitation
All members of 2009 UNC Freshman class invited to survey
Incentive: iPod touch, 30 gift cards
30.57% Response (RR2), n=1,198
Descriptive statistics: Facebook use, privacy, activity
Multivariate models Analysis
Research Question 3
Page 28
Variables Employed in Regression Analysis
Predictors: 1. Social network site socio-informational processes (SNS-SIP) scale α = .8948
2. Social network site support (SNS-S) scale α = .8900
Predictors
Individual: Gender, NC residency, stress (CES-D, PSS)
Environmental: Roommate and hallmate quality, Facebook efficacy
Support: Local and Facebook network size
Controls
Social Support: Barrera’s Index of Sosically Ssupportive Behaviors (ISSB)
Adaptation to college: Baker and Siryk’s Student Adaptation to College Question-naire (SACQ)
Outcome
Research Question 3
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
Finding 1: Relationship between SNS, Support, and Adaptation
Research Question 3
Page 30
Finding 2: SEM model of SNS, Support, and Adaptation
Research Question 3
Page 31
Finding 2: SEM model of SNS, Support, and Adaptation
RMSEA: 0.056, CFI: 0.799, TLI: 0.7990
Research Question 4
Page 32
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
How are SNS integrated into everyday life information seeking during transition?
Theoretical Framework
Page 33
Adaptation to Transition
Integration Into Trans.
Environment
Management of Stress
Socio- Informational Processes
Development of Support Network
Access to Social
Support e.g. Ashforth, 2001; Cohen & Wills, 1985; Cowan, 1991; Ebaugh, 1988; Ensel & Lin, 1991
Research Question 4
Page 34
How are SNS integrated into everyday life information seeking during transition?
Research Question 4
Page 35
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
Research Question 4
Page 36
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
Research Question 4
Page 37
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
Review: Research Questions
Page 38
What factors are associated with the structure of transitional socio-technical networks?
What factors are associated with the growth of transitional socio-technical networks?
Does SNS use during transition increase adaptation to transition?
How are SNS integrated into everyday life information seeking during transition?
1
2
3
4
Four primary questions, employing three data sets
Limitations
Page 39
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
Contributions
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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)
Implications and Future Directions
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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
Implications and Future Directions
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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)
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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