Invited research overview: end-user programming
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Enterprise information mashups: integrating information, simply
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Why we twitter: understanding microblogging usage and communities
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
CHI '08 Extended Abstracts on Human Factors in Computing Systems
Wishful search: interactive composition of data mashups
Proceedings of the 17th international conference on World Wide Web
What do we "mashup" when we make mashups?
Proceedings of the 4th international workshop on End-user software engineering
Damia: data mashups for intranet applications
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Growth of the flickr social network
Proceedings of the first workshop on Online social networks
Mining social tags to predict mashup patterns
SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
Constrained wiki: the Wikiway to validating content
Advances in Human-Computer Interaction
Socially-Enriched semantic mashup of web APIs
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
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Mashup allows users to integrate different kinds of sources together. The ProgrammableWeb.com is a popular online social mashup site that enables users to publish mashups. In this paper, we discover user behavior pattern in mashup community by studying the network and clustering properties of ProgrammableWeb.com. Moreover, we define a new concept--mashup entropy to evaluate the diversity of mashup community. The results prove that mashup community possesses scale-free property. The frequently used APIs and annotated tags attract large amounts of users. People who have similar ideas tend to have similar behavior. Finally, we find that the overall mashup entropy decreases as time goes by, which means that users tend to reuse several design patterns in creating mashups.