Abstract
This paper investigates the structure and dynamics of the Web 2.0 software ecosystem by analyzing empirical data on web service APIs and mashups. Using network analysis tools to visualize the growth of the ecosystem from December 2005 to 2007, we find that the APIs are organized into three tiers, and that mashups are often formed by combining APIs across tiers. Plotting the cumulative distribution of mashups to APIs reveals a power-law relationship, although the tail is short compared to previously reported distributions of book and movie sales. While this finding highlights the dominant role played by the most popular APIs in the mashup ecosystem, additional evidence reveals the importance of less popular APIs in weaving the ecosystem’s rich network structure.
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O’Reilly, T.: Web 2.0: Compact Definition? (2005), http://radar.oreilly.com/archives/2005/10/web-20-compact-definition.html
Wikipedia: Mashup, http://en.wikipedia.org/wiki/Mashup_web_application_hybrid
Cho, A.: An Introduction to Mashups for Health Librarians. JCHLA 28, 19–22 (2007)
Kulathuramaiyer, N.: Mashups: Emerging Application Development Paradigm for a Digital Journal. JUCS 13, 531–542 (2007)
O’Brien, D.S., Fitzgerald, B.F.: Mashups, Remixes and Copyright Law. INTLB 9(2), 17–19 (2006)
Goodman, E., Moed, A.: Community in Mashups: The Case of Personal Geodata (2006), http://mashworks.net/images/5/59/Goodman_Moed_2006.pdf
Jackson, C., Wang, H.J.: Subspace: Secure Cross-domain Communication for Web Mashups. In: 16th International World Wide Web Conference, pp. 611–620 (2007)
Liu, X., Hui, Y., Sun, W., Liang, H.: Towards Service Composition Based on Mashup. In: 2007 IEEE Congress on Services, pp. 332–339 (2007)
Hinchcliffe, D.: Is IBM Making Enterprise Mashups Respectable? (2006), http://blogs.zdnet.com/Hinchcliffe/?p=49
Barabási, A.-L., Albert, R.: Emergence of Scaling in Random Networks. Science 286, 509–512 (1999)
Anderson, C.: The Long Tail (2004), http://www.wired.com/wired/archive/12.10/tail.html
Watts, D.J., Strogatz, S.H.: Collective Dynamics of “Small-World” Networks. Nature 393, 409–410 (1998)
Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge Univ. Press, Cambridge (1994)
Borgatti, S.P.: NetDraw: Graph Visualization Software. Analytic Technologies (2002)
Adamic, L.A.: Zipf, Power-Laws, and Pareto: A Ranking Tutorial, http://www.hpl.hp.com/research/idl/papers/ranking/ranking.html
Brynjolfsson, E., Hu, Y.J., Smith, M.D.: From Niches to Riches: Anatomy of the Long Tail. Sloan Mgmt. Rev. 47(4), 67–71 (2006)
Kilkki, K.: A Practical Model for Analyzing Long Tails. First Monday 12(5) (2007)
Berlind, D.: Mashup Ecosystem Poised to Explode (2006), http://blogs.zdnet.com/BTL/?p=2484
Hinchcliffe, D.: The Web 2.0 Mashup Ecosystem Ramps Up (2006), http://web2.socialcomputingmagazine.com/the_web_20_mashup_ecosystem_ramps_up.htm
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Yu, S., Woodard, C.J. (2009). Innovation in the Programmable Web: Characterizing the Mashup Ecosystem. In: Feuerlicht, G., Lamersdorf, W. (eds) Service-Oriented Computing – ICSOC 2008 Workshops. ICSOC 2008. Lecture Notes in Computer Science, vol 5472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01247-1_13
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DOI: https://doi.org/10.1007/978-3-642-01247-1_13
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