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

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Published on September 10, 2013

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The 5th IEEE International Conference on Social Computing (SocialCom 2013) / Washington, DC, USA / 10th September 2013
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© 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. Breslin owen.sacco@deri.org & john.breslin@nuigalway.ie ASE/IEEE SocialCom 2013 Washington, DC, USA Tuesday 10th September 2013

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme Introduction  Current Social Networks:  Provide generic privacy settings for sharing information  Do not take user’s trust into account

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme Introduction In reality, we only share parts of our information with whomever we trust

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme 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

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme 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?

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme 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

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme 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

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme 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%

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme 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%

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme 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

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme  How often do you share content from external sources within Facebook, Google+, Twitter and LinkedIn? User Survey: Usage Patterns

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme User Survey: Usage Patterns  How often do you re-share or retweet what other users share within Facebook, Google+, Twitter and LinkedIn?

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme User Survey: Usage Patterns  How often do you use the like, +1 and favourite buttons on Facebook, Google+, Twitter and LinkedIn?

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme User Survey: Usage Patterns  For what do you use the like, +1 and favourite buttons on Facebook, Google+, Twitter and LinkedIn?

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme User Survey: Usage Patterns  How often do you comment or reply on Facebook, Google+, Twitter and LinkedIn?

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme User Survey: Usage Patterns  How often do you tag or mention other users on Facebook, Google+, Twitter and LinkedIn?

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme User Survey: User’s Trust Perception  What is your perception of the meaning of the word “Trust”?

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme User Survey: User’s Trust Perception  What do you trust when you share external content into Facebook, Google+, Twitter and LinkedIn?

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme User Survey: User’s Trust Perception  What do you trust when you re-share or retweet content within Facebook, Google+, Twitter and LinkedIn?

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme User Survey: User’s Trust Perception  What do you trust when you like, +1, or favourite within Facebook, Google+, Twitter and LinkedIn?

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme User Survey: User’s Trust Perception  What do you trust when you comment or reply to posts within Facebook, Google+, Twitter and LinkedIn?

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme User Survey: User’s Trust Perception  What do you trust when you tag or mention other users within Facebook, Google+, Twitter and LinkedIn?

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme User Survey: User’s Trust Perception  What do you trust when you are tagged or mentioned within Facebook, Google+, Twitter and LinkedIn?

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme User Survey: Summary  Overall Participants’ Activity of Social User Interactions

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme User Survey: Summary  Overall Participants’ Perception of Trust

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme 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: » denotes the user’s subjective trust value for a particularτ 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

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme 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: » denotes the user’s subjective trust value for a particularτ 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

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme 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): » denotes the user’s subjective trust value for a particularτ requester » r denotes the number of likes, +1s, favourites, comments, replies and tags related to the user and the requester

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme 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

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme 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

INSIGHT Centre for Data Analytics www.insight-centre.org Semantic Web & Linked Data Research Programme Thanks! @owensacco owen.sacco@deri.org @johnbreslin john.breslin@nuigalway.ie

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