innovation in the programmable web
characterizing
the mashup
ecosystem
Shuli Yu ‐ Singapore Management University
for Mashups ’08 @ ICSOC

a

is made of…
+ integrate

is made of…
API
+ integrate
Mashup
API
registered in
and these are

the

m ashup

s napshot
s APIs
Network intervals
:
th
@ 6 mon 007
to Dec 2
Dec 2005
m

m API
m
m
API
API m
m
API
2‐mode network

m API
m
m
API
API m
m
API
mashup
ecosystem

m API
m
m
API
API m
m
API
2664 mashups594 APIs

what are the characteristics?
m API
m
m
API
API m
m
API
growth structure
patterns

growth...
mashups per month
20 APIs per month

apis ranked

apis ranked
top 20 APIs

top 20 APIs

power law

long

Chris Anderson (2004): The Long Tail, Wired

Kalevi Kilkki (2007): A practical
model for analyzing long tails, First Monday
share of total volume total volume
covered by objects up to
rank x
factor that defines the form
the number of objects
that cover half of the
whole volume

pareto rule
20% of the causes result in
of the effects

pareto rule?
20% of top APIs have created
of the mashups

another observation…
51% of all APIs have
no mashups
>4 mashups
3 mashups
0 mashups 2 mashups
1 mashup

18% 4% 8% 15% 51%
>4 3 2 1 0 mashups
long

0.68 0.86
exponent:
x16
APIs with
1 mashup
x9
top API:
Google Maps

API
m API m
m
m API
m
API m
API API
m m
m m m
API
m
m
m
API
API m API
API
m
m
API
structure?

social network analysis
node repulsion

dec 2005

jun 2006

dec 2006

jun 2007

dec 2007

dec 2007 again

API Tier 2:
Social/Community,
API Tier 1: Search
Google popular APIs
Many
Maps
API Tier 3:
Feeds, blogging, online
retail, music, video
Less popular APIs

keystone

keystones
business strategy:
create and (2) share value
(1)
by creating platform
services, tools or technologies
that offer solutions to
others
Iansiti and Levien (2004): Strategy as ecology

platform APIs
mapping, search, community
data APIs
news, pictures, videos, music, shopping

so… what matters?
type of service
a mashup provides
affects its compatibility
others
with

so… what else could matter?
existing popularity
time (age)
rating
security
licensing model
protocols and data formats

regressions
time series
analysis

what makes an API successful?
how to determine what role and
position in the network is most
appropriate?
to think about.

and many thanks, also, to
Jason Woodard – John Musser – Darshan Santani

the extras

Bala Iyer (2007)