Network Architectures & Services

Transcription

1 Network Architectures & Services Fernando Kuipers Multi-dimensional analysis Network peopleware Network software Network hardware Individual: Quality of Experience Friends: Recommendation Global: Online Social Networks Processes: Viruses, tweets, Algorithms: Routing, SDN, Big data: Mining & analysis Complex networks: Internet, energy, brain, optical networks, Network design: Robustness vs. cost

2 Not only Happiness is Contagious Online Social Network Analysis in the Context of a Changing Communication Paradigm in Telecommunications Norbert Blenn TU Delft - Network Architectures and Services (NAS)

3 The Change of Communication Paradigms The challenge is not just in understanding the technology, but also the fundamental shifts in human communication behavior. (IBM Institute for Business Value analysis) Market direction many to many collaborative point to point conversational

4 Effects of the Change of Communication Paradigms (TeleGeography Report) Year Skype s international 2.9 % 4.4 % 8 % 13 % 34 % call market share

5 Effects of the Change of Communication Paradigms Open Internet provider-controlled traditional communication shared social space

6 Telecommunication and Online Social Network Analysis How to benefit from the change in communication? Big data analysis and the combination of Big Data to (Big Data) n in order to create new services and value cases New services through mobility analysis Real-time feedback through social sensors Product or company placement in the social media landscape Recommendation systems

7 Users of Online Social Networks as Social Sensors Mobility-Networks Identifying regions in which individuals travel/use mobile servives enables location based services and valuable results for other economic sectors. Living Restaurants Shopping Work Traces of two users from Eindhoven Clusters generated based on mobility during weekends

8 Users of Online Social Networks as Social Sensors Real-time feedback of product/company placement Vodafone KPN Words related to Vodafone Words related to both Words related to KPN "Context-Sensitive Sentiment Classification of Short Colloquial Text", N. Blenn, C. Doerr, K. Charalampidou and P. Van Mieghem, IFIP Networking 2012

9 Users of Online Social Networks as Social Sensors Combination of Big Data into (Big Data) n Sentiment analysis of tweets negative positive

10 Word-Of-Mouth in Online Social Networks Contagious opinions and recommendations Influential users: are more central, have high betweenness, having a higher effectivity Groups of people are more effective than single users "Lognormal Infection Times of Online Information Spread", C. Doerr, N. Blenn, and P. Van Mieghem, 2013, PLoS ONE

11 Word-Of-Mouth in Online Social Networks Contagious opinions The more friends forward a message, the more likely the friend will adopt "Are Friends Overrated? A Study for the Social Aggregator Digg.com", C. Doerr, N. Blenn, S. Tang and P. Van Mieghem, Computer Communications, 2012.

12 Understanding Interests of Individuals Recommendation systems Knowing more about the user than he/she himself Inferring interests based on friends "How much do your friends know about you? Reconstructing private information from the friendship graph ", N. Blenn, C. Doerr, N. Shadravan and P. Van Mieghem, Eurosys 2012, 5th Workshop on Social Network Systems

13 Telecommunication and Online Social Network Analysis Reliable information because of (Big Data) n Our Datasets / Big Data Twitter: 3 billion Messages (ca. 200 new per second), 6.1 billion edges (friendship relations), 120 million profiles Hyves: 5.8 million profiles, 90 million edges (friendship relations) IMDB: 178,000 movies, 2million comments (complete) Digg: 2 million profiles, 7.7 million edges, 315 million votes (complete) Sourceforge: 100,000 projects, 460,000 user (complete)

14 What did he just say? Conclusion Understanding the shift in people s communication pattern states a high potential to create new untapped value Knowing how customers behave and how they interact will be the key driver in the future to remain competitive Thinking out of the Box Network and content analysis can predict trends as (Influential users and groups can be found when approached the right way). (Big Data) n is the potential for the telecom industry as no one else except companies in the telecom sector have access to all necessary datasets

15 You found the last slide. References: "Crawling and Detecting Community Structure in Online Social Networks using Local Information", N. Blenn, C. Doerr, S. van Kester and P. Van Mieghem, 2012, IFIP Networking 2012, May 21-25, Prague, Czech Republic. "Metric Convergence in Social Network Sampling", C. Doerr and N. Blenn, 2013, SIGCOMM 2013, the 5 th ACM HotPlanet Workshop "Lognormal infection Times of online information spread", C. Doerr, N. Blenn, and P. Van Mieghem, 2013, PLoS ONE (to appear) "Are Friends Overrated? A Study for the Social Aggregator Digg.com", C. Doerr, N. Blenn, S. Tang and P. Van Mieghem, Computer Communications, 35(7), pp , DOI /j.comcom , 2012 "Context-Sensitive Sentiment Classification of Short Colloquial Text", N. Blenn, C. Doerr, K. Charalampidou and P. Van Mieghem, 2012, IFIP Networking 2012, May 21-25, Prague, Czech Republic. "Digging in the Digg Social News Website"; S. Tang, N. Blenn, C. Doerr and P. Van Mieghem, 2011; IEEE Transactions on Multimedia, Vol. 13, No. 5, October, pp "How much do your friends know about you? Reconstructing private information from the friendship graph ", N. Blenn, C. Doerr, N. Shadravan and P. Van Mieghem, 2012, Eurosys 2012, 5th Workshop on Social Network Systems "Lognormal Distribution in the Digg Online Social Network"; P. Van Mieghem, N. Blenn and C. Doerr, 2011, The European Physical Journal B, Vol. 83, No. 2, pp "Content Propagation in Online Social Networks"; N. Blenn, C. Doerr, P. Van Mieghem, ICTOpen 2011 "Characterizing the Structure of Affiliation Networks", D. Liu, N. Blenn and P. Van Mieghem, 2012, 12th International Conference on Computational Science (ICCS), June 4-6, Omaha, Nebraska, USA. A Social Network Model Exhibiting Tunable Overlapping Community Structure", D. Liu, N. Blenn and P. Van Mieghem, 2012,1st International Workshop on Advances in Computational Social Science, June 4-6, Omaha, Nebraska, USA. Delft University of Technology, Faculty of Electrical Engineering Dept. of Intelligent Systems, Mekelweg 4, 2628 CD Delft Room: EWI , Tel: , Mail: [email protected]