Utilizing social context for providing personalized services to mobile users A EuroSSC 2010 presentation Athanasios Karapantelakis and Gerald Q. Maguire.

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Presentation transcript:

Utilizing social context for providing personalized services to mobile users A EuroSSC 2010 presentation Athanasios Karapantelakis and Gerald Q. Maguire Jr. Royal Institute of Technology (KTH), Stockholm Sweden. Industrial sponsor: Conformiq Inc

Agenda Introduction System overview Measurements and results Q&A session

Introduction (1/2) Trends in social media usage today – Increase in social network usage, blogging and community sites. Users spend more time online browsing Social Networks, than reading [1] – Social network users going mobile [2] – Commercial application “After friends and family, the number one driver for brand trust is online reviews and feedback from the social media space”. [3] Social Technologies Gain Traction In The Enterprise – Year: 2010 Will Be The Year Of differentiation for vendors to stay relevant. [4] – Personalized social networking in the center of next-generation social networking platforms Mark Zuckerberg: “Facebook is part of the shift toward more social and personalized experiences everywhere online.” [5] [1] eMarketer: More Time Spent on Social Media than Worldwide: most common daily activity, but social racks up more hours [2] ComScore inc. - Facebook and Twitter Access via Mobile Browser Grows by Triple-Digits in the Past Year, March [3] The Nielsen Company – Friending the Social Consumer, June 16, [4] Forrester Research - Enterprise Social Networking 2010 Market Overview [5] Mark Zuckerberg - Building the Social Web Together April 21,

Introduction (2/2) Challenge: how to take advantage of the abundance of social context available online, to proactively provide personalized content to users. Problem outline: – Social context is dispersed in different non-interoperable social networks [1]. – Personalized content is provided to the users superficially (e.g. friend recommendations, group publications, recommendations based on loose criteria etc.). Proposed Solution: – (1) A context-aware system which aggregates social context, to synthesize user profiles and recommend Web feeds of related content to users. – (2) A user mobile application which receives web feeds and presents them to the user in an intuitive way. Multiple dimensions in the solution: – System architecture – Information aggregation and modeling – Criteria of selection [1] Economist Print Edition: Online social networks: Everywhere and nowhere, March 2008.

System overview Original Implementation: Karapantelakis, A. and Devlic, A. and Zarifi Eslami, M. and Khamit, S. Printing in Ubiquitous Computing Environments. In: 6th International Conference on Ubiquitous Intelligence and Computing, 7-9 Jul 2009, Brisbane, Australia. Service Agents (Content Providers) Applications (iOS app) Context Sources (Social Networks) Context Broker SUBSCRIBENOTIFY Content PUBLISH

Context Broker Raw Context Modeling: FOAF & custom RDF-based schemas create a user profile. – Certain context transcoded with the help of web domain knowledge to produce more meaningful results. Maintain Subscription Base: – Based on SIP/SIMPLE Decision Algorithm – Triggered every time an incoming feed arrives. – Calculates how the new feed matches each of the user profiles stored in the system. – If the calculation shows a match for a given profile, the feed is forwarded to the user application via a NOTIFY message.

User Application

Measurements (1/5) Exposed system for public use, for a 6-month period. – 462 users participated during that time. – Privacy concerns: TOS requested users for permission to access personal information for anonymous statistical analysis. Measured system performance and perceived user experience. – Preliminary results

Measurements (2/5)

Measurements (3/5)

Measurements (4/5) Reinforcing a statement

Measurements (5/5) Percieved User Experience measurements

Conclusion Presented a system for aggregating social context for personalized context. – Relevant with current trends. – System exposed to public use for 6 months. – Large dataset of traces after exposing the system for public use allows for further investigation Future enhancements – Taking advantage of social relations between people (friendships, business affiliations, etc.)

Thanks for attending ! Q&A Session