The Social Hourglass: Enabling Socially- aware Applications and Services. Adriana Iamnitchi University of South Florida

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1 The Social Hourglass: Enabling Socially- aware Applications and Services Adriana Iamnitchi University of South Florida

2 Much Social Information Available Connects people through relationships Object centric: use of same objects Person centric: declared relationships or co- participation in events, groups, etc.

3 Scenario 1: CallCensor 3

4 Scenario 2: Sofa Surfer 4

5 Scenario 3: Data Placement 5

6 Current Approach: Vertically Integrated Socially- aware Applications Spam filtering Sybil identification Personalized search Target marketing Medical emergency notifications

7 So, What s Wrong? Application- limited collection and use of social information High bootstrap cost Limited (potentially inaccurate) information. E.g., Information from online social networks Hidden incentives to have many friends All relationships equal Symmetric relationships Newer proposals to merge different sources of social (and sensor) information for one app 7

(potentially inaccurate) information. E.g.

8 Our Proposal: An Infrastructure for Social Computing Sofa Surfer Roommate Finder CallCensor

9 We want an infrastructure that: Can fuse information from various sources Existing or future Allow user to control own information What is collected Where it is stored Who can access it Provide social knowledge to a variety of applications: Social inferences (may be non- trivial) The Social Hourglass: an Infrastructure for Socially- aware Applications and Services, Iamnitchi et al., IEEE Internet Computing, May/June

a variety of applications: Social inferences (may be non- trivial) The Social Hourglass: an Infrastructure

10 The Social Hourglass Architecture Applications Sofa Surfer Roommate Finder CallCensor Applications make use of so Social Inference A PI knowledg social Social knowledge service pro social data. Stored da Social Data Mstoring anagement applications throu A1 A2 Personal A ggregators Personal aggregators collect A3 sensor ou S11 S21 S22 S32 S33 S43 SocialS sensors analyze socia Social ensors social relat Social signals encod Social Signals 10

Stored da Social Data Mstoring anagement applications throu A1 A2 Personal A ggregators Personal aggregators

11 Social Sensors Consume existing social signals Location Collocation Schedule (e.g., Google calendar) Mobile phone activity (calls, sms) Online social network interactions Personal relations (family) Shared content Shared interest (e.g., CiteULike) 11

12 Work in Progress: Social Sensor for Gaming Interactions What s difficult: Variability in playing habits Variability in playing skills Time patterns CDF All II I III IV Number of events per minute Average number of events Gameplay Edge creations Lower 95% ci Upper 95% ci Sun Mon Tue Wed Thu Fri Sat Average number of edge creations

1 0 IV 10-6 10-5 10-4 10-3 10-2 10-1 10 0 10 1 10 2 Number of events per minute Average number of events 3000 2500 2000 1500

13 Aggregators Act as the user s personal assistant Runs on trusted device (cell phone) Responsible for Managing passwords for various applications Personalization Identity management Carol Bob's Identity Manager Carol carol@work.com User1 User2 carol@home.com Alice's Identity

Personalization Identity management Carol Bob's Identity Manager Carol

14 The Social Hourglass Architecture Applications Sofa Surfer Roommate Finder CallCensor Applications make use of so Social Inference A PI knowledg social Social knowledge service pro social data. Stored da Social Data Mstoring anagement applications throu A1 A2 Personal A ggregators Personal aggregators collect A3 sensor ou S11 S21 S22 S32 S33 S43 SocialS sensors analyze socia Social ensors social relat Social signals encod Social Signals 14

15 Social Graph 15

16 Distributed Social Graph 16

17 Prometheus Architecture Prometheus: User- Controlled P2P Social Data Management for Socially- Aware Applications, Kourtellis et al., Middleware

18 Social Inference Functions The social graph management service exports an API that implement social inferences 18

19 API for Applications: Social Inference Functions 5 basic social inference functions: relation_test (ego, alter, ɑ, w) top_relations (ego, ɑ, n) neighborhood (ego, ɑ, w, radius) proximity (ego, ɑ, w, radius, distance) social_strength (ego, alter) More complex functions can be built 19

(ego, ɑ, n) neighborhood (ego, ɑ, w, radius) proximity (ego, ɑ, w,

20 Social Strength Quantifies strength between ego and alter Result normalized to consider overall activity Search all paths of maximum 2 social hops One approach to quantify social strength. Others are certainly possible. 20

Search all paths of maximum 2 social hops One approach

21 Thank you! Work funded by US National Science Foundation grants CNS and CNS

On the Design of Socially-Aware Distributed Systems. Nicolas Kourtellis

On the Design of Socially-Aware Distributed Systems by Nicolas Kourtellis A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Computer