Research Meeting

2009. 3. 12Seungseok Kang

Center for E-Business TechnologySeoul National University

Seoul, Korea

Copyright 2008 by CEBT

Introduction

Device-Centric Social Network Model on Mobile Environment

Social Network Model

– Sociometric data modeling

– Graph representation

– Centrality and centralization

– Correspondence analysis

Issues on Mobile Environment

– Various types of devices

– High mobility of users

– Power consuming and caching

– Device clustering

Service Types

– Collaborative filtering with user’s association regarding the issues of mobile environment

Copyright 2008 by CEBT

Social Network Model

Sociometric data modeling

Components, cores, and cliques

Networks and relations

Positions, roles, and clusters

Blockmodeling (1992~)

– Knowing the structure of a network

– Facilitating the understanding of network phenomena

Graph representation

Sociogram (1932~)

– A classic approach to display sociometric data

– directed graph with nodes, edges, and adjacency matrix

Random Graph Model

– For multiple network of relations with dependencies

Copyright 2008 by CEBT

Social Network Model (cont’d)

Centrality and centralization

Local and global centrality of social network

– Degree-based measure

– Closeness and betweenness

Group centrality (1999~)

– Normalized group degree

Adjacency-based measurement

– Two-mode Centrality

Regarding different kind of data Actors and events / binary relation (membership or participation)

– Core-periphery measures

Calculating coreness by using core-periphery structure

Correspondence analysis

Researches on affiliation network

– The decomposition of a matrix into its basic structure

Copyright 2008 by CEBT

Issues on Mobile Environment

Initial characteristics of social network on mobile environment

Small-world phenomenon

– The average length of the shortest path between devices may be different

Various types of devices

graph representation scheme

Understanding the characteristics of devices which is able to be distinguished from entities of traditional social network model

High mobility of users

Density calculation

– Dynamic change of device’s density

Decentralized problem

– Devices may be distributed more sparsely than people

– May need to adapt extended centralization scheme

Power consuming and caching

Similar to caching issues in sensor network

Ganesh Santhanakrishnan et al., “towards Universal Mobile Caching”, MobiDE’05

Device clustering

Context-awareness

Expanding existing representation scheme with context

Copyright 2008 by CEBT

Service Types

What will we do within device-centric social network?

Context-aware services

– Context caching

– Context abstraction

– Dynamic device clustering with context information

Collaborative Filtering

– Regarding the association or correspondence between devices

Copyright 2008 by CEBT

Papers

WWW Conference referred track – social networks & Web 2.0

Analysis of Social Networks & Online Interaction

– Parag Singla et al., “Yes, There is a Correlation – From Social Networks to Personal Be-havior on the Web”, WWW 2008

– Vicenc Gomez et al., “Statistical Analysis of the Social Network and Discussion Threads in Slashdot”, WWW 2008

– Lada A. Adamic et al., “Knowledge Sharing and Yahoo Answers: Everyone Knows Some-thing”, WWW 2008

Discovery and Evolution of Communities

– Xin Li et al, “Tag-based Social Interest Discovery”, WWW 2007

– Jure Leskovec et al., “Statistical Properties of Community Structure in Large Social and Information Networks”, WWW 2008

Others

Jon Kleinberg, “The Convergence of Social and Technological Networks”, ACM Communications, 2008

Souvik Debnath, “Festure Weighting in Content Based Recommendation System using Social Network Analysis”, WWW 2008 poster paper

Frank Edward Walter et al, “A model of a trust-based recommendation system on a social network”, Auton Agent Muti-Agent System, Springer, 2008

Copyright 2008 by CEBT

Issues

Huge gap between the researches and practical services

Group Centrality, Blockmodeling, Sociogram, …vs

Cyworld.com, MySpace.com, Facebook.com, …

In most cases, online social network service have not depended on theoretical algorithms or social network model

– They build and use their own social network according to their service types and business process

– Their social network model may be able to be analyzed with traditional re-searches, but there are still such a big gap between theoretical results and practical services

– What should we focus on?

Analyzing the current online social network based on traditional approaches and extending the algorithms within the existing online social network service model such as Facebook.com

Suggesting a new theory (or framework, algorithms, whatever) by analyzing the problems or limitation of previous theoretical research issues

……