“I Like” - Analysing Interactions within Social Networks to Assert the Trustworthiness of Users, Sources and Content

Copyright 2013 INSIGHT Centre for Data Analytics. All rights reserved.

INSIGHT Centre for Data Analytics www.insight-centre.org

Semantic Web & Linked Data Research Programme

“I Like” – Analysing Interactions within Social Networks to Assert the

Trustworthiness of Users, Sources and Content

Owen Sacco & John G. [email protected] & [email protected]

ASE/IEEE SocialCom 2013Washington, DC, USA

Tuesday 10th September 2013



Introduction

Current Social Networks: Provide generic privacy settings for sharing information Do not take user’s trust into account



Introduction

In reality, we only share parts of our information with whomever

we trust



Social Factors

Trust judgments are influenced by Social Factors:

Past interactions with a person Opinions of a person’s actions Other people’s opinions Rumours Psychological factors impacted over time Life events and so forth

These can be hard to compute since the information required is limited and unavailable in Social Networks



Research Questions

1. What is the user’s perception of trust?

2. Which information extracted from Social Networks is useful for computing trust?

3. For what and for whom can trust be computed from the information in Social Networks?



User Survey

To analyse how trust can be inferred from Social Networks

We focus on whether trust can be asserted from user interactions within the Social Networks

User interactions with: Other users Content shared within the Social Networks



User Survey

User interactions:

Sharing of content from external sources

Re-sharing or retweeting content

“Like”, or “+1” or “favourite”

Comments or replies

Tags or mentions



User Survey

178 participated in the survey: 65% male and 35% female

Age:

Social Network Accounts:

Age Category Participants

18 - 20 3%

21 - 29 45%

30 - 39 32%

40 - 49 13%

50 - 59 6%

60+ 1%

Social Networks Participants

Facebook 88%

Google+ 69%

Twitter 82%

LinkedIn 85%

None of the Above 1%



User Survey

Occupations of participants

Occupation Categories Participants

Computer and Mathematics 59%

Education, Training and Library 26%

Business and Financial 13%

Management 8%

Architecture and Engineering 6%

Arts, Design, Entertainment, Sports and Media 5%

Life, Physical and Social Sciences 3%

Office and Administrative Support 2%

Healthcare Support 1%

Community & Social Service 1%

Sales 1%

Unemployed 1%



User Survey

Two parts: 1. Usage Patterns

2. User’s Trust Perception in Social Networks

Usage Patterns: how often users use each social user interaction and on which Social Network

User’s Trust Perception: analyses what users trust when they use these social user interactions



How often do you share content from external sources within Facebook, Google+, Twitter and LinkedIn?

User Survey: Usage Patterns




How often do you re-share or retweet what other users share within Facebook, Google+, Twitter and LinkedIn?




How often do you use the like, +1 and favourite buttons on Facebook, Google+, Twitter and LinkedIn?




For what do you use the like, +1 and favourite buttons on Facebook, Google+, Twitter and LinkedIn?




How often do you comment or reply on Facebook, Google+, Twitter and LinkedIn?




How often do you tag or mention other users on Facebook, Google+, Twitter and LinkedIn?



User Survey:User’s Trust Perception

What is your perception of the meaning of the word “Trust”?




What do you trust when you share external content into Facebook, Google+, Twitter and LinkedIn?




What do you trust when you re-share or retweet content within Facebook, Google+, Twitter and LinkedIn?




What do you trust when you like, +1, or favourite within Facebook, Google+, Twitter and LinkedIn?




What do you trust when you comment or reply to posts within Facebook, Google+, Twitter and LinkedIn?




What do you trust when you tag or mention other users within Facebook, Google+, Twitter and LinkedIn?




What do you trust when you are tagged or mentioned within Facebook, Google+, Twitter and LinkedIn?



User Survey:Summary

Overall Participants’ Activity of Social User Interactions



User Survey:Summary

Overall Participants’ Perception of Trust



Asserting Trust:Trusting the Source

Trust for the source can be asserted from: The share button The re-share or retweet buttons

Trusting the source:

» τ denotes the user’s subjective trust value for a particular source

» w denotes the trust a third party user has in the user’s social graph

» s denotes the number of shares and re-shares related to the source



Asserting Trust:Trusting the Content

Trust for content can be asserted from: The share button The re-share or retweet buttons The like, +1 and favourite buttons

Trusting the content:

» τ denotes the user’s subjective trust value for a particular content

» w denotes the trust value a third party user has in the user’s social graph

» c denotes the number of shares, re-shares, likes, +1s and favourites related to the content



Asserting Trust:Trusting the User

Trust for the user (i.e. requester) can be asserted from: The like, +1 and favourite buttons The comments or replies to posts The tags of the requester tagged by the information owner The tags of the information owner tagged by the requester

Trusting the user (i.e. requester):

» τ denotes the user’s subjective trust value for a particular requester

» r denotes the number of likes, +1s, favourites, comments, replies and tags related to the user and the requester



Conclusion & Future Work

We focused on: Analysing the user’s perception of trust and How trust can be inferred from Social Networks

User survey that analysed the usage patterns and the user’s trust perception of: The share button The re-share or retweet buttons The like, +1 or favourite buttons The comment or reply buttons The tag or mention buttons/options



Conclusion & Future Work

The results have revealed that users are concerned with asserting trust for: The source that created the content The content The user requesting personal information

Future work: Implementing the trust assertions in our Privacy

Preference Framework (see previous publications)– To enforce privacy preferences based on these trust

assertions



Thanks!

@[email protected]

@[email protected]

Technology

“I Like” - Analysing Interactions within Social Networks to Assert the Trustworthiness of Users, Sources and Content