Phithakkitnukoon, Santi and Dantu, Ram
Due to copyright restrictions, this file is not available for public download
Click here to request a copy from the OU Author.
|DOI (Digital Object Identifier) Link:||https://doi.org/10.1007/s00146-009-0230-5|
|Google Scholar:||Look up in Google Scholar|
Social data mining has become an emerging area of research in information and communication technology fields. The scope of social data mining has expanded significantly in the recent years with the advance of telecommunication technologies and the rapidly increasing accessibility of computing resources and mobile devices. People increasingly engage in and rely on phone communications for both personal and business purposes. Hence, mobile phones become an indispensable part of life for many people. In this article, we perform social data mining on mobile social networking by presenting a simple but efficient method to define social closeness and social grouping, which are then used to identify social sizes and scaling ratio of close to “8”. We conclude that social mobile network is a subset of the face-to-face social network, and both groupings are not necessary the same, hence the scaling ratios are distinct. Mobile social data mining.
|Item Type:||Journal Article|
|Copyright Holders:||2009 Springer-Verlag London Limited|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Depositing User:||Santi Phithakkitnukoon|
|Date Deposited:||13 Nov 2012 11:26|
|Last Modified:||06 Oct 2016 04:54|
|Share this page:|