COMPUTATIONAL TIE STRENGTH: THEORY AND APPLICATIONS Eric Gilbert’s Prelim
kevin casey lucas leslie
TIE STRENGTH concept & impact The strength of a tie is a (probably linear) combination of the amount of TIME , the emotional INTENSITY , the INTIMACY (mutual con fi ding), and the reciprocal SERVICES which characterize the tie. — Granovetter STRONG TIES are the people you really trust. WEAK TIES , conversely, are merely acquaintances.
TIE STRENGTH concept & impact 7,000+ papers cite TSOWT fi rms with right mix of ties get better deals strong ties can affect mental health
USING IT in design & analysis MODEL TIE STRENGTH TO… 1 build more informed privacy controls. 2 make better friend introductions. 3 rethink social streams. 4 analyze large-scale, networked phenomena.
USING IT in design & analysis MODEL TIE STRENGTH TO… 1 build more informed privacy controls. 2 make better friend introductions. 3 rethink social streams. 4 analyze large-scale, networked phenomena.
Tie strength is a blind spot in social media.
Tie strength is a blind spot in social media. This thesis will show how to RECONSTRUCT it from digital traces, and how to apply it as a DESIGN and ANALYTIC tool.
HEURISTICS a sample of substitutes communication reciprocity [19] Friedkin 1980 one mutual friend [56] Shi, Adamic & Strauss 2007 communication recency [41] Lin, Dayton & Greenwald 1978 interaction frequency [22] Gilbert, Karahalios & Sandvig 2008 [17] Fischer, et al. 2006
HEURISTICS the difference CHI 2009 MODEL 88% Adj. R 2 = 0.53 MSGS → FRIEND 62% Adj. R 2 = 0.09 BASELINE 52%
COMPUTATIONAL TIE STRENGTH PART ONE
DIGITAL TRACES our interactions leave marks
THE MAPPING PROBLEM
RESEARCH QUESTIONS R1. The literature suggests seven dimensions of tie strength: INTENSITY , INTIMACY , DURATION , RECIPROCAL SERVICES , STRUCTURAL , EMOTIONAL SUPPORT and SOCIAL DISTANCE . As manifested in social media, can these dimensions predict tie strength? In what combination? R2. What are the limitations of a tie strength model based SOLELY on social media?
THE DATA overview 2,184 assessed friendships from 35 university students & staff described by 70+ numeric indicators
ASSESSING TIE STRENGTH participant interface
STATISTICAL METHODS
THE MODEL performance 1 87.6% accuracy χ 2 (1, N = 4368) = 700.9 + p < 0.001 μ + 0 μ 0 1
DELIVERABLES part one multicollinearity & structure tough dimensions … new techniques the predictors vs. accuracy tradeoff fi ve fl avors of tie strength
DESIGNING AROUND TIE STRENGTH PART TWO
RESEARCH QUESTIONS R1. How GENERAL is the tie strength model? Does it work in a new medium, like Twitter? R2. Can automatically-inferred tie strength usefully INFORM DESIGN in the real world? Can it help the collapsed context problem? R3. Can feedback from users IMPROVE the model? If so, how does it change?
THE COLLAPSED CONTEXT PROBLEM collision of social circles which normally remain separate
We Meddle demo
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RELATED SYSTEMS socially-rendered interfaces [62] Whittaker, et al. 2004. [17] Fischer, et al. 2006
METHODS how general is the model? can feedback improve it?
METHODS can tie strength usefully inform design? QUALITATIVE EVALUATION with We Meddle’s users 10 – 20 semi-structured interviews centered on usage and utility
TIE STRENGTH & DIFFUSION PART THREE
TIE STRENGTH its potential in diffusion studies Dichotomous distinctions [edge exists or not] can sometimes be misleading … a weighted graph representation will frequently be more appropriate. More studies that assess the effectiveness of such approximations — and provide concrete, empirically validated guidelines for practice within particular problem domains — would be a welcome addition to the literature. — 2009 Science article “Revisiting the Foundations of Network Analysis”
DIFFUSION every link is equal Fowler & Christakis. 2008. Dynamic Spread of Happiness … BMJ. Ivkovic & Weisbenner. 2007. Information Diffusion Effects in Individual Investors' Common Stock Purchases … Rev. Fin. Kossinets, Kleinberg & Watts. 2008. The Structure of Information Pathways in a Social Communication Network. KDD. Onnela, et al. 2007. Structure and Tie Strengths in Mobile Communication Networks. PNAS.
WEIGHTED DIFFUSION from Onnela, et al.
RESEARCH QUESTIONS R1. Does tie strength modulate the fl ow of information through a network? R2. Does tie strength interact with content as it fl ows through a network? R3. If tie strength regulates information fl ow through a network, how does this affect macroscopic properties of diffusion?
METHOD the retweet
METHOD value-laden content 1 link per 700 tweets ⇒ 1000–1500 users
COMPUTATIONAL TIE STRENGTH: THEORY AND APPLICATIONS Eric Gilbert
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