DocumentCode :
589049
Title :
What Makes Communities Tick? Community Health Analysis Using Role Compositions
Author :
Rowe, Matthew ; Alani, H.
Author_Institution :
Knowledge Media Inst., Open Univ., Milton Keynes, UK
fYear :
2012
fDate :
3-5 Sept. 2012
Firstpage :
267
Lastpage :
276
Abstract :
Today´s Web is social and largely driven by a wide variety of online communities. Many such communities are owned and managed by businesses that draw much value from these communities, in the form of efficient and cheaper customer support, generation of new ideas, fast spreading of information, etc. Understanding how to measure the health of online communities and how to predict its change over time, whether to better or to worse health, is key to developing methods and policies for supporting these communities and managing them more efficiently. In this paper we investigate the prediction of community health based on the social behaviour exhibited by their members. We apply our analysis over 25 SAP online communities, and demonstrate the feasibility of using behaviour analysis to predict change in their health metrics. We show that accuracy of health prediction increases when using community-specific prediction models, rather than using a one-model-fits-all approach.
Keywords :
Internet; behavioural sciences; business data processing; prediction theory; social networking (online); SAP online communities; Web; business management; cheaper customer support; community health analysis; community health prediction; community-specific prediction models; health metrics; health prediction; idea generation; one-model-fits-all approach; role compositions; social behaviour; worse health; Atmospheric measurements; Business; Communities; Current measurement; Particle measurements; Social network services; behaviour; community health; composition derivation; data mining; prediction; roles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Privacy, Security, Risk and Trust (PASSAT), 2012 International Conference on and 2012 International Confernece on Social Computing (SocialCom)
Conference_Location :
Amsterdam
Print_ISBN :
978-1-4673-5638-1
Type :
conf
DOI :
10.1109/SocialCom-PASSAT.2012.18
Filename :
6406255
Link To Document :
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