Fred Stutzman Dissertation Defense

Networked InformationBehavior in Life TransitionFred StutzmanPh.D. Defense, December 8, 2010

Outline of the TalkNetworked 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. behaviorConclusions and   Identification of limitations and conclusions limitations   Future directions for researchPage  2

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, invaluablePage  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 populationPage  4

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, 1991Page  5

Research ThemeThis 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

Research QuestionsFour 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

Research Question 1Factors 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

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

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

Research Question 1Finding 2: What factors are associated with theproduction 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.Page  12

Research Question 1Finding 2: What factors are associated with theproduction of ties in a transitional network? Gender MajorPage  13

Research Question 1Finding 3: Do the strength of the associativefactors 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

Research Question 2Factors 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 analysesPage  15

Research Question 2 Marlow, 2009Page  17

Research Question 2Dependent Variable: Log of UNC FriendsPage  18

Research Question 2Control 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 StatusPage  19

Research Question 2Indepdendent 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 laggedPage  20

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

Research Question 2Findings 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 < .05Page  22

Research Question 2Finding 2: Predicted TrajectoriesPage  23

Research Question 3Does 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 modelPage  24

Research Question 3Does 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 collegePage  26

Research Question 3Survey 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 modelsPage  27

Research Question 3Variables 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

Research Question 3Finding 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 adaptationPage  29

Research Question 3Finding 2: SEM model of SNS, Support, and AdaptationPage  30

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

Research Question 4How are SNS integrated into everyday life information seeking duringtransition? 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 analysisPage  32

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

Research Question 4Finding 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 transitionPage  35

Research Question 4Finding 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 awarenessPage  36

Research Question 4Finding 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 distractionPage  37

Review: Research QuestionsFour 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

LimitationsLimitations 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 dataPage  39

ContributionsContributions 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

Implications and Future DirectionsNext 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 periodPage  41

Implications and Future DirectionsNext 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

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

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.Page  44

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Fred Stutzman Dissertation Defense

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