1. Emotional Response and Bridging ties on Social Networks Interpreting how Individual Attributes and Social Graph Properties intervene in the Surprise Response in Information Sharing Digital Media Research Methods Porto, DiMe 24 th May 2013 Motivations Overview Research Question Literature Review Research Methods Desired Contributions Suggestions Carlos Figueiredo

2. Motivation  Make a contribution to solve the problem of the ‘Portfolio Effect’ on Recommender System (e.g. content recommendation).  Measure novelty in an information flow.  Propose a methodology to measure and predict the delivering of novelty.

3. Overview  Content-Based “You bought, liked or shared a bunch of things like Y” Recommender Systems  Collaborative Filtering “People like you bought, liked or shared Y”  Trust-Based CF “People who bought, liked or shared X also bought, liked or shared Y” e.g. Friend Network (Fb); Reputation Network (Ebay) (1) (2) e.g. Amazon (1)coding the genome of each song; (2)listen to other users’ radio stations (Friends, Neighbors, Groups)

4. Overview Recommenders my proposal  Recommendation based on novelty.  Novelty delivering based on users attributes and in the social graph properties.  Surprise response as a proxy of the Novelty to design the framework.

5. Literature Review  Novelty delivering. Bridging ties  Dimensions implied on novelty. Emotional response (Surprise) Tie strength (between receptor and source of information) Homophily (similarities) Centrality (structural location in the social network) topics of research

6. Literature Review Bridging Ties  The Strength of Weak Ties (Granovetter 1973) All bridges are weak ties. Not all weak ties are bridges. Strong ties can be a bridge if such ties do not share ties with other individuals of the same clique. novelty delivering How to deliver novelty?

7. Literature Review Bridging Ties  Structural Holes (Burt 1992) Tie strength does not determine the information potential brought by a bridging tie. Structural holes linked by actors determine the information potential.  Ties established by non- redundant links between actors. novelty delivering Structural Holes and Weak Ties (Burt 1992)  Weak ties and Structural holes (McEvily et al. 1999)

8. Literature Review Emotional response  Ten primordial emotions (DES scale of Izard) (Izard 1991)  Emotions start with a process of cognitive appraisal (Finkenauer et al. 1998).  Novelty is one fundamental type of appraisal (e.g., Scherer 1984; Smith and Ellsworth 1987).  Surprise is a specific consequence of the appraisal of novelty (Finkenauer et al. 1998). Can I predict novelty? dimensions implied on novelty

9. Literature Review Measuring tie strength  Amount of time, intimacy, intensity and reciprocal services (Granovetter 1973).  Closeness (Marsden et al. 1984).  Emotional support (Wellman and Wortley 1990).  Intensity and valence (Petrosky 2011). dimensions implied on novelty What makes a tie be strong?

10. Literature Review Homophily  Demographic and Attitudinal similarities Status homophily  Background factors (economic status), gender, religion and ethnicity (McPherson et al. 2001). Attitudinal homophily  Perceived Homophily Measure (McCroskey et al. 1975; 2006). Why some weak ties are not bridges? dimensions implied on novelty

11. Literature Review Homophily  Cognitive similarities based on: Music genres Reflective and Complex, Intense and Rebellious, Upbeat and Conventional, and Energetic and Rhythmic (Rentfrow and Gosling 2003). Emotional reaction to music genres. Similarities on information interests. Similarities on emotional reaction to the information accessed. Equal preferences on content posted (survey). dimensions implied on novelty

12. Literature Review Centrality Degree; betweeness; closeness (Freeman 1979)  Centrality and information flow (Borgatti et al. 2009; Mori et al. 2010)  Centrality and friendship network (Opshal 2010; Afuah 2013) Can I predict structural location? dimensions implied on novelty

13. Research questions  Does surprise define bridging ties?  Can similarities in individual attributes and structural location in the network determine the stimulus of surprise?

14. Hypothesis  H1 – Is more likely that an individual become surprised by a weak tie than by a strong tie.  H2 – The non redundancy between ties is predictor of surprise.  H3 – The degree of homophily justifies the conditions that make someone weakly tied to another person acting as a bridge.  H4 – Users' popularity is independent of the novelty appraisal by the receptors.

15. Research Methods  Survey Emotional response, particularly on surprise Ties strength Homophily  SPSS Statistics (Logistic regression; Multivariate regression; Mann-Whitney test)

16. Research Methods  NodeXl Centrality variables (degree; betweeness; closeness) Graph 1 - Emotional reaction to information sharing Graph 2 – Friendship network

17. Desired contribution  Emotional reaction as a relevant property for social networks analysis.  A methodology that identifies bridging ties and characterizes the delivering of novelty based in the stimulus of surprise.   A framework for recommendation systems based on weak ties as recommenders of surprising information or of new perspectives.

18. Suggestions  Comments are welcome…  Thank you. Carlos Figueiredo