Title :
Users´ classification and usage-pattern identification in academic social networks
Author_Institution :
Inf. Technol. Dept., AlBalqa Appl. Univ., Assalt, Jordan
Abstract :
Academic social networking sites are becoming increasingly popular. Several groups of academic people at different level of their career and from different disciplines are utilizing them for their benefit. This paper aims to explore usage patterns of an academic Social Networking Site (SNS) (namely Academia.edu) by different groups of academic users. It gains its importance because of the lack of academic social networking sites studies especially those concerning different user types and usage patterns of academic social networking sites.
Keywords :
educational administrative data processing; pattern classification; social networking (online); Academia.edu; academic social networking sites; usage-pattern identification; user classification; user types; Art; Chemistry; Computer science; Engineering profession; Materials; Medical services; Social network services; Collaborative software; Facebook; Human computer interaction; LinkedIn; Social Network;
Conference_Titel :
Applied Electrical Engineering and Computing Technologies (AEECT), 2011 IEEE Jordan Conference on
Conference_Location :
Amman
Print_ISBN :
978-1-4577-1083-4
DOI :
10.1109/AEECT.2011.6132525