Predicting Tie Strength with Social Media Eric Gilbert and Karrie Karahalios CHI 2009 Based on the authors’ slide deck

Slides:



Advertisements
Similar presentations
Tie Strength. Strong vs. Weak Ties Strong ties Trusted Close friends and family Weak ties Often part of other social circles Acquaintances, co-workers.
Advertisements

The Strength of Weak Ties
Mobile Communication Networks Vahid Mirjalili Department of Mechanical Engineering Department of Biochemistry & Molecular Biology.
Keele Management School
Gallup Q12 Definitions Notes to Managers
Emotional Response and Bridging ties on Social Networks Interpreting how Individual Attributes and Social Graph Properties intervene in the Surprise Response.
Predicting Tie Strength with the Facebook API Tasos Spiliotopoulos Madeira-ITI, University of Madeira, Portugal / Harokopio University, Greece Diogo Pereira.
Λ14 Διαδικτυακά Κοινωνικά Δίκτυα και Μέσα Strong and Weak Ties Chapter 3, from D. Easley and J. Kleinberg book.
Designing Research Concepts, Hypotheses, and Measurement
Based on chapter 3 in Networks, Crowds and markets (by Easley and Kleinberg) Roy Mitz Supervised by: Prof. Ronitt Rubinfeld November 2014 Strong and weak.
Paid Staff and Volunteers: Do Their Attitudes Differ? Riikka Teikari and Christeen George Abstract The aim of the present study was to explore whether.
Professional Development
Work motivation among healthcare professionals in the Saudi hospitals Presented by Nouf Sahal Al-Harbi Supervised by: Dr. Saad Al-Ghanim 2008.
Measurement  The process whereby individual instances within a defined population are scored on an attribute according to rules Usually given a numeric.
BUSINESS AND FINANCIAL LITERACY FOR YOUNG ENTREPRENEURS: EVIDENCE FROM BOSNIA-HERZEGOVINA Miriam Bruhn and Bilal Zia (World Bank, DECFP)
Centre for Materials Physics Presentation by Peter Byrne Creating and using Strong Passwords Superconductivity Group.
Modeling Relationship Strength in Online Social Networks Rongjian Xiang 1, Jennifer Neville 1, Monica Rogati 2 1 Purdue University, 2 LinkedIn WWW 2010.
Research Problem: Father involvement plays important role in development of a child; for fathers who are incarcerated; presents challenges that seem insurmountable.
The financial practices and perceptions behind separate systems of household financial management Dr Katherine Ashby, Faculty of Law and Social Sciences,
MULTIPLE REGRESSION. OVERVIEW What Makes it Multiple? What Makes it Multiple? Additional Assumptions Additional Assumptions Methods of Entering Variables.
AN INTRODUCTION TO PORTFOLIO MANAGEMENT
Lecture 9 – Leader-Member Exchange (LMX) Theory
Simple Regression correlation vs. prediction research prediction and relationship strength interpreting regression formulas –quantitative vs. binary predictor.
Coye Cheshire & Andrew Fiore June 30, 2015 // Computer-Mediated Communication Online Communities.
Bivariate & Multivariate Regression correlation vs. prediction research prediction and relationship strength interpreting regression formulas process of.
“Make New Friends, but Keep the Old” - Recommending People on SN sites Jilin Chen, Werner Geyer, Casey Dugan, Michael Muller, Ido Guy CHI2009 June 1, 2011.
Social Networks Abhimanyu DhamijaAbhishek Kumar Munish MiniaPriyank Sharma.
Employee Engagement Survey
Defining and Measuring Variables Slides Prepared by Alison L. O’Malley Passer Chapter 4.
Celeste M. Schwartz, Ph.D. Montgomery County Community College Blue Bell, Pennsylvania
ASSOCIATION BETWEEN INTERVAL-RATIO VARIABLES
Managing Your Social Capital Priscilla Arling University of Minnesota, Carlson School of Management – AWCTC March 2005.
Chapter 2 Modified from: Barringer & Ireland (2006) Recognizing Opportunities and Generating Ideas Part II.
Section 7.3 ~ Best-Fit Lines and Prediction Introduction to Probability and Statistics Ms. Young.
Confidence Intervals for the Regression Slope 12.1b Target Goal: I can perform a significance test about the slope β of a population (true) regression.
CS 599: Social Media Analysis University of Southern California1 Social Ties and Information Diffusion Kristina Lerman University of Southern California.
CHAPTER 15 Simple Linear Regression and Correlation
Data Mining and Machine Learning Lab Network Denoising in Social Media Huiji Gao, Xufei Wang, Jiliang Tang, and Huan Liu Data Mining and Machine Learning.
Wasanthi Madurapperuma Social Network of Entrepreneurs & Small Business Growth Related Literature & Research Gap Unit of Analysis - Small Retail Businesses.
Data Analysis (continued). Analyzing the Results of Research Investigations Two basic ways of describing the results Two basic ways of describing the.
1 The Spatial Dimension of Social Capital: An Exploration Zong-Rong Lee 李宗榮 Institute of Sociology Academia Sinica Taipei, Taiwan.
Extension to Multiple Regression. Simple regression With simple regression, we have a single predictor and outcome, and in general things are straightforward.
BMW Creative Benchmarking May About Newspaper Creative Benchmarking.
Advanced Methods and Analysis for the Learning and Social Sciences PSY505 Spring term, 2012 April 25, 2012.
Day 3: Sampling Distributions. CCSS.Math.Content.HSS-IC.A.1 Understand statistics as a process for making inferences about population parameters based.
ANOVA and Linear Regression ScWk 242 – Week 13 Slides.
Special Topics in Educational Data Mining HUDK5199 Spring 2013 March 25, 2012.
Zoran Bohaček Croatian Quants Day 22. II Business reasons to analyse a credit registry database.
SW388R6 Data Analysis and Computers I Slide 1 Multiple Regression Key Points about Multiple Regression Sample Homework Problem Solving the Problem with.
World Health Organization Gender and Women’s Health Challenges of a short module in surveys on other topics vs a specialized survey Henrica A.F.M. Jansen.
Studying Community Dynamics CS 294h – 9 FEB 2010.
WANG Ying, PAN Mianzhen , LU Lu , MAO Jiye Renmin University of China.
Personal Control over Development: Effects on the Perception and Emotional Evaluation of Personal Development in Adulthood.
Network Data and Measurement Peter V. Marsden Presented by Peilin(Emily) Sun Feb 23 rd, 2015.
Online students’ perceived self-efficacy: Does it change? Presenter: Jenny Tseng Professor: Ming-Puu Chen Date: July 11, 2007 C. Y. Lee & E. L. Witta (2001).
Adaptive Integrated Framework (AIF): a new methodology for managing impacts of multiple stressors in coastal ecosystems A bit more on AIF, project components.
Selected Topics in Data Networking Explore Social Networks: Center and Periphery.
Safe and active life as pupils’ experience Survey study for 5th and 7th grade students in Turku.
26134 Business Statistics Week 4 Tutorial Simple Linear Regression Key concepts in this tutorial are listed below 1. Detecting.
Imposed Group Structures Chapter 9. Overview Background Information Background Information Structural PerspectiveStructural Perspective Input VariablesInput.
Diane M. Sullivan (2007) Recognizing Opportunities and Generating Ideas Part II Entrepreneurial Networks and Evolutionary Creativity: The Nexus of Opportunity.
Nature Mama A work in Progress By Michael Reilley.
Social Media Recommendation based on People and Tags (SIGIR2010) IBM Research Lab Ido Guy,Naama Zwerdling Inbal Ronen,David Carmel,Erel Uziel.
26134 Business Statistics Week 4 Tutorial Simple Linear Regression Key concepts in this tutorial are listed below 1. Detecting.
Romantic Partnerships and the Dispersion of Social Ties: A Network Analysis of Relationship Status on Facebook By: Lars Backstrom - Facebook Inc, Jon Kleinberg.
Social Networks Analysis
What is the Meaning of Life?
7.3 Best-Fit Lines and Prediction
John Thompson, Ph.D. Buffalo State College
Confidence and Prediction Intervals
Presentation transcript:

Predicting Tie Strength with Social Media Eric Gilbert and Karrie Karahalios CHI 2009 Based on the authors’ slide deck

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 confiding), 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 Social support offered by strong ties improves mental health (Schaefer 1990) Banks with right mix of ties get better financial deals (Uzzi 1999) Weak ties benefits job-seekers (Granovetter 1974) vs. job seeker from lower socioeconomic backgrounds often benefits from strong ties (Granovetter 1983) Employees who weakly tie themselves beyond organization boundaries tend to receive better performance reviews and generate more creative ideas (Burt 2004) Weak ties act as a conduit for useful info, but they often use a few media vs. strong ties’ diversified communication channels (Haythornthwaite 1998, 2002)

TIE STRENGTH: dimensions AT WHAT POINT is a tie to be considered weak? … Do all four indicators count equally toward tie strength? — D. Krackhardt In theory, tie strength has at least seven dimensions – GRANOVETTER’S intensity, intimacy, duration & services – WELLMAN’S emotional support – LIN’S social distance – BURT’S structural Peter Marsden used survey data from three metropolitan areas to unpack predictors of tie strength (Marsden 1990) Marsden, P. V. and Campbell, K. E Measuring Tie Strength. Social Forces, 63(2), 482–501.

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 Facebook users: 35 university students & staff – Firefox ext. Greasemonkey to guide participants through a randomly selected subset of their Facebook friends Rated 62.4 friends (SD: 16.2); total 2,184 friends

DATA COLLECTION: methodology

PREDICTIVE VARIABLES Intensity (communications)

PREDICTIVE VARIABLES intimacy LIWC dictionary to perform content analysis (intimacy categories)

PREDICTIVE VARIABLES Structural Duration

PREDICTIVE VARIABLES reciprocal services emotional support (URLs) LIWC dictionary to perform content analysis (intimacy categories)

PREDICTIVE VARIABLES social distance

STATISTICAL METHODS For each friend I of user X: – si: tie-strength (bet. X~i) – Ri: predictive variables, Di: interactions – N(i): mutual friends’ (of X & i) structural scores Xi sisi j

THE MODEL: structure & performance

MOST PREDICTIVE by |beta|

THE MODEL: details 87.2% accuracy X2(1, N = 4368) = p < 0.001

LIMITATIONS: high residuals Ah yes. This friend is an old ex. We haven't really spoken to each other in about 6 years, but we ended up friending each other on Facebook when I first joined. But he's still important to me. We were best friends for seven years before we dated. So I rated it where I did (I was actually even thinking of rating it higher) because I am optimistically hoping we’ll recover some of our “best friend”-ness after a while. Hasn't happened yet, though. error: ~0.5

LIMITATIONS: high residuals We were neighbors for a few years. "I babysat her child multiple times. She comes over for parties. I'm pissed off at her right now, but it's still 0.8. ";) Her little son, now 3, also has an account on Facebook.“ We usually communicate with each other on Facebook via her son's account. This is our “1 mutual friend.” error: ~0.5

IMPLICATIONS: for theory Social network analyses of large-scale phenomena (beyond links) Weights on dimensions & importance of structure (interactions among variables) Is there an upper bound? Do important things get left out?

IMPLICATIONS: for practice MODEL TIE STRENGTH TO… – prioritize activity updates. – broadcast especially novel information. – make better friend introductions. – build more informed privacy controls.

Summary A MODEL of tie strength SPECIFIC WEIGHTS on tie strength’s dimensions THE ROLE OF STRUCTURE in modulating tie strength