My chapter in “Computing with Social Trust”

Computing with Social TrustThe book “Computing with Social Trust” is out. In it you can find a chapter by Paolo Avesani and myself about my PhD work on Trust in Recommender Systems. You can download my chapter or buy the dead-tree book from Amazon. Following you can find the Table of contents. Enjoy!


Table of Contents

1. Introduction to Computing with Social Trust
Jennifer Golbeck

1. The Need for Social Trust

2. Challenges to Computing with Social Trust

3. Future Questions

4. Conclusions


Part I Models of Social Trust

2. Examining Trust, Forgiveness and Regret as Computational Concepts
Stephen Marsh and Pamela Briggs

1. Introduction

2. Why is Trust Important? Why a Formalization?

3. A Parable of The Modern Age

4. A Brief Sojourn to ‘Human Factors’: Why Not Call it

5. Trust After All

6. Trust as Was

7. What Can’t Trust Give Us?

8. Trust As Is, Part Zero: The Dark Side

1. Distrust

2. Mistrust

3. Untrust

4. Ignorance is

5. The Continuum, Revisited

6. Continuing a Difficult Relationship

9. Regret

1. What Regret Is

2. The Many Faces of Regret

3. Modeling Regret

10. Trust as Is, Part One: Building Regret into Trust

11. Forgiveness and The Blind and Toothless

1. What Forgiveness Is

2. A Model of Forgiveness

12. Trust As Is, Part Two: The Incorporation of Forgiveness

1. The Trust Continuum, Revised: The Limits of

2. Forgiveness

13. Applications: Revisiting the Parable and Imagining the Future

1. The Parable at Work

2. Regret Management

14. Related Work

15. Trust as Will Be: Future Work and Conclusions


3. A non-reductionist approach to trust
Cristiano Castelfranchi, Rino Falcone, and Emiliano Lorini

1. Introduction

2. Desiderata for a logical model of social trust

3. A logic for trust reasoning

1. Syntax and semantics

2. Axiomatization

3. Possibility orders over formulas

4. Execution preconditions for action execution

4. A formal ontology of Trust

1. Core trust

2. Distrust, lack of trust and mistrust

3. Delegation and decision to trust

5. Comparative trust

6. Conclusion


4. Social Trust of Virtual Identities
Jean-Marc Seigneur

1. Introduction

1. Identity Terminology

2. Computational Trust Terminology

2. Flawed Trust Computation due to Simplistic Identity Approach

1. Computational Trust under Identity Usurpation and Multiplicity Attacks

2. Remaining ASUP Issues due to Identity Shortcomings

3. Entification: Bridging Trust and Virtual Identities

1. Recognition rather than Authentication

2. End-to-End Trust

3. Means for Recognition Adaptation

4. Encouraging Privacy and Still Supporting Trust

5. Accuracy and Attack-Resistance of the Trust Values

4. Entification Framework Evaluation

1. Trust Transfer Applied to the Email Domain

2. ASUP Evaluation

5. Conclusion


Part II Propagation of Trust

5. Attack resistant trust metrics
Raph Levien

1. Introduction

2. Attack resistance

1. Redundant certification paths

3. 3 Group trust metric

1. Proof of attack resistance

4. Implementation in Advogato

5. Eigenvector trust metrics

1. Stochastic model of PageRank

2. Attack resistance of PageRank

3. Advogato’s eigenvector metric


6. On Propagating Interpersonal Trust in Social Networks
Cai-Nicolas Ziegler

1. Introduction

2. Trust in Social Networks

1. Classification of Trust Metrics

2. Semantic Web Trust

3. Local Group Trust Metrics

1. Outline of Advogato Maxflow

2. Appleseed Trust Metric

3. Comparison of Advogato and Appleseed

4. Parameterization and Experiments

5. Implementation and Extensions

6. Testbed for Local Group Trust Metrics

4. Distrust

1. Semantics of Distrust

2. Incorporating Distrust into Appleseed

5. Discussion

6. Acknowledgements


7. The Ripple Effect: Change in Trust and Its Impact over a Social Network
Jennifer Golbeck and Ugur Kuter

1. Introduction

2. Trust Inference Algorithms

1. Local vs Global

2. Central Authority vs. Group vs. Individual

3. Computation Methods

3. Algorithms Studied

1. Inference Algorithms Based on Matrix Arithmetic

2. Network-Path Inference Algorithms

4. Experimental Setup

5. Results

1. Number and Distance of Changes

2. The Magnitude of Change

3. Influence of the Network Structure

4. Other Changes in Trust Inference

6. Discussion and Conclusions


Part III Applications of Trust

8. Eliciting Informative Feedback: The Peer-Prediction Method
Nolan Miller and Paul Resnick and Richard Zeckhauser

1. Introduction

2. A Mechanism for Eliciting Honest Feedback

1. The Base Case

2. Eliciting Effort and Deterring Bribes

3. Voluntary Participation and Budget Balance

3. Extensions

1. Sequential Interaction

2. Continuous Signals

4. Issues in Practical Application

1. Risk Aversion

2. Choosing a Scoring Rule

3. Estimating Types, Priors, and Signal Distributions

4. Taste Differences Among Raters

5. Non-Common Priors and Other Private Information

6. Other Potential Limitations

5. Conclusion


6. Proofs

7. Eliciting Effort


9. Capturing Trust in Social Web Applications
John O’Donovan

1. Introduction

2. Research on Trust in the Social Web

3. Trust Sources on the Social Web

4. Source 1: Modeling Trust from Ratings in ACF Recommender Systems

1. Combining Trust in ACF

2. Capturing Profile-Level & Item-Level Trust

3. Trust-Based Recommendation

4. Evaluation

5. Building Trust

6. Recommendation Error

7. Discussion

5. Source 2: Extracting Trust From Online Auction Feedback Comments

1. The AuctionRules Algorithm

6. Evaluation

1. Setup

2. Comparing AuctionRules With Machine Learning Techniques

3. Coverage and Distribution Experiments

7. Discussion

8. Source 3: Extracting Trust through an Interactive Interface

1. Fair Representation of Genre Information

2. Visualising Trust Relations in PeerChooser

3. Implementation

9. Evaluation

1. Experimental Data

2. Rating Distributions

3. Procedure

4. Recommendation Accuracy

10. Comparison of different Trust Sources

11. Conclusions


10. Trust Metrics in Recommender Systems
Paolo Massa and Paolo Avesani

1. Introduction

2. Motivations

3. Our proposal: Trust-aware Recommender Systems

1. Trust networks and trust metrics

2. An Architecture of Trust-aware Recommender Systems

3. How trust alleviates RS weaknesses

4. Related work

4. Empirical validation

1. Dataset used in experiments: Epinions

2. New evaluation measures

3. Results of the experiments

5. Discussion of results

6. Conclusions


11. Trust and Online Reputation Systems
Ming Kwan and Deepak Ramachandran

1. Introduction

1. What is trust?

2. The Complex World of Online Trust

1. Learning to gauge intention

2. Evaluating and Validating Competence

3. Web 1.0 vs. Web 2.0

1. How can it help me?

4. The New Model of Online Trust

5. Reputation

1. Trouble in Paradise – the SAP Developer Network

2. When to use reputation as the basis for trust

6. Relationship

1. Social Networking

2. Opening up APIs

3. Exploiting the value of social networks

4. share...and lend

5. Sponsored Groups

6. When to use relationship as the basis for trust

7. Process

1. Caught in the act - reinforcing process

2. So What?

3. When to use process as the basis for trust

8. A recipe for online trust based on three ingredients


12. Internet Based Community Networks: Finding the Social in Social Networks
K. Faith Lawrence

1. Introduction

2. Defining Community in the Age of Social Networks

3. Visualising Community

4. Communities, Groups and Networks

5. Community Trust

6. Conclusion

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