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A Survey of Trust in Social Networks WANITA SHERCHAN, IBM Research-Australia SURYA NEPAL and CECILE PARIS CSIRO ICT Centre Presented by Jacob Couch.

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Presentation on theme: "A Survey of Trust in Social Networks WANITA SHERCHAN, IBM Research-Australia SURYA NEPAL and CECILE PARIS CSIRO ICT Centre Presented by Jacob Couch."— Presentation transcript:

1 A Survey of Trust in Social Networks WANITA SHERCHAN, IBM Research-Australia SURYA NEPAL and CECILE PARIS CSIRO ICT Centre Presented by Jacob Couch

2 Trust Definitions

3

4 Trust Origin Trust in Psychology ● Trust is considered to be a psychological state of the individual, where the trustor risks being vulnerable to the trustee based on positive expectations of the trustee’s intentions or behavior. ● Cognitive ● Emotive ● Behavioral

5 Trust Origin Trust in Sociology ● Trust is considered to be a bet about the future contingent actions of the trustee. ● Considered a level of expectation within a group. ● Cognitive ● Behavioral ● Emotive builds over time

6 Trust Origin Trust in Computer Science User Trust ● Inherently personalized ● Based on previous experience ● Direct Trust – Based on interactions between users of a system. – Strength is determined based on frequency. ● Recommended Trust – Experiences of Direct Trust are reflected to neighbors based on experience and sociability

7 Trust Origin Trust in Computer Science System Trust ● “The expectation that a device or system will faithfully behave in a particular manner to fulfill its intended purpose” – TPM

8 Trust Definitions Trust Types/Facets ● Calculative ● Relational ● Emotional ● Cognitive ● Institutional ● Dispositional Trust Properties ● Context Specific ● Dynamic ● Propagative ● Non-transitive ● Composable ● Subjective ● Asymmetric ● Self-reinforcing ● Event Sensitive

9 Calculative ● “Calculation on behalf of the trusted designed to maximize the trustor's stakes in the interaction” ● Typical economic model

10 Relational ● Trust built up over time. ● Typically used in employee relationships

11 Emotional ● “The perceived outcome of direct interpersonal relationships [sic]”

12 Cognitive ● “Trust based on reason and relational behavior” – Information channels – Norms – Sanctions ● “Positive referrals … increase cognitive trust in the trustee”

13 Institutional ● “Trust derived from a provided environment that encourages cooperation and penalizes misbehaviors [sic]”

14 Dispositional ● “...over the course their lives, people develop generalized expectations about the trustworthiness of other people”

15 Properties of Trust ● Context Specific ● Dynamic ● Propagative ● Non-transitive ● Composable ● Subjective ● Asymmetric ● Self-reinforcing ● Event Sensitive

16 Context Specific ● “Trust is context specific in its scope” ● Would you trust your mechanic to be your dentist?

17 Dynamic ● “Trust can increase or decrease with new experiences” ● As a relationship decays, the amount of trust typically decreases

18 Propagative ● “Alice trusts Bob who in turn trusts John” – Alice can derive some amount of trust on John ● Trust can be based on the friend of a friend mode, but it is not transitive

19 Non-transitive ● “Alice trusts Bob who in turn trusts John” – This does not imply that Alice trusts Bob

20 Composable ● Alice trusts Bob and Charlie. Charlie trusts John. Bob trusts John – Trust through propagation can be composed to create a greater trust.

21 Subjective ● Social trust is subjective to the rater. ● If Alice thinks that Bob's opinions are good, John may not think that Bob's opinions are good.

22 Asymmetric ● Trust is asymmetric between members of a relationship. – The amount that Alice trusts Bob is not the same amount Bob trust Alice

23 Self-reinforcing ● “Members act positively with other members whom they trust. ● “if the trust between two members is low... it is unlikely that they will interact”

24 Event Sensitive ● “Trust take a long time to build, but a single high-impact event may destroy it completely”

25 Trust Models Trust Models ● Statical/machine learning – Artificial Neural Networks – Hidden Markov Models ● Heuristics ● Behavior based

26 Social Networks

27 Social Network Examples

28 Properties - Homophilly ● Social pattern to associate with similar others ● Social properties include race, ethnicity, age, religion, eduction, occupation...

29 Properties - Small-world phenomenon ● The concept of the “Kevin Bacon” effect. – All persons are connected within 6 degrees

30 FOAF - Friend of a Friend FOAF - Friend of a Friend ● Most modern social networks use friend of a friend as a boundary of private information. ● The underlying, but not necessarily correct, assumption is that friendships are transitive.

31 Social Capital ● No universal agreeable definition ● “... a collective resource that facilitates cooperation at the small group level.... no longer resides with an individual but exists through relationships between actors... is based on the density of interactions... ”

32 Social Trust ● Aspect of social capital that represents cooperative infrastructure. ● “By analogy with notions of physical capital and human capital—tools and training that enhance individual productivity— ‘social capital’ refers to features of social organization such as networks, norms, and social trust that facilitate coordination and cooperation for mutual benefit.”

33 Process of Social Trust

34 Trust Information Collection ● Attitudes ● Behaviors ● Experiences

35 Attitudes ● “And individuals degree of like or dislike” ● Affect – Emotional response that indicates personal preference ● Behavior – Tendency of an individual ● Cognition – Beliefs about an object

36 Experiences ● Perception of members through interactions ● Must be measured through feedback

37 Behaviors ● Patterns of interactions ● Trust is the community is measured by the frequency of interaction

38 Evaluation of Social Trust ● Network Structure/Graph-Based Trust Models ● Interaction-Based Trust Models ● Hybrid Trust Models

39 Network Structure/Graph Requires feedback from user on interactions ● Golbek proposes FOAF rating on a scale of 1-9 ● Ziegler/Hang propose method to calculate trust between two groups of people on aggregate of ratings ● Caverlee proposes feedback rating mechanism after each social interaction ● Maheswaran proposes social trust based on ratings plus social network connectivity

40 Interaction Bases model purely on interactions of members ● Nepal proposes model on popularity trust and engagement trust ● Adali proposes model based on conversation trust and propagation trust

41 Hybrid Combines Network structure and Interactions

42 Trust Dissemination ● Trust Based Recommendation Models – Provide per object recommendations to user ● Visualization – Provide visualization to user to show trustworthiness of members for general consumption

43 Trust Definitions

44 Analysis

45 Analysis

46  Computer Science trust is normally numerical and comparing against a threshold, Sociological and psychological responses should also be evaluated.  Properties such as asymmetry, self- reinforcement, and event sensitivity are typically not evaluated in the trust equation.

47  Evaluation of Tie-Strength  Visualization of Trust ◦ Can be used to help service providers identify healthy and unhealthy networks  Resistance to malicious attacks in P2P systems

48 Conclusion ● Trust models in modern online social networks are still very primitive ● Human social network properties can be ported to online social, thus allowing the use of existing sociological research ● Social capital can be used to cultivate trust of an online social network


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