Abstract
We propose FAME (inFluencer Apis in developer coMmunitiEs), a multi-dimensional influencer model for APIs in service-oriented environments. We define influence as the extent to which an API is likely to be adopted in mashups and service-oriented applications. The proposed model helps providers increase the visibility of their APIs and developers select the best-in-class APIs. We extract more than eighteen textual and non-textual API features from various programming communities such as GitHub, StackOverflow, HackerNews, and ProgrammableWeb. We perform sentiment analysis to quantify developers' opinions towards using APIs. We introduce a cumulative API influence score to measure the influence of APIs across communities and categorize APIs into tiers based on their influence. We introduce a linear regression technique to predict the evolution of influence scores and correlate API features to those scores. We conduct experiments on large and real-world data-sets extracted from the above mentioned programming communities to illustrate the viability of our approach.