Does the First Mover Advantage Exist on GitHub?

TL;DR

This paper investigates whether first movers on GitHub gain lasting influence, finding early adopters tend to accumulate more followers, but social behaviors and aging effects can counteract this advantage.

Contribution

It introduces an empirical method to analyze influence dynamics on GitHub, highlighting the existence of early adopter advantages and the factors that can diminish this effect.

Findings

Early adopters tend to have more followers in the long run

Social networking behavior of late adopters can influence influence dynamics

Aging effects of repositories impact user influence over time

Abstract

Collaborative consensus-finding is an integral element of many Web services and greatly determines the quality of information, content, and products that are available through the Web. That also means that the dynamics of democratic consensus-finding strengthen collective resilience against potential threats that attempt to degrade information, content, and products and affect Web data, users, behaviors, and even beyond as well as offline life. Even on Web platforms that are open to all, the influence of some first mover authors may shape future discussion and collaboration, which is comparable to academic citation networks for instance. In a social coding network such as GitHub, activities of a set of users can have influence on other users who can get interested in further actions, possibly contributing to a new project together with influential users. In this paper, we analyze the effect of contribution activities on gaining influence in this and comparable networks that provide users the functionality and aims for reaching collaborative goals on the Web.For this purpose, we present an empirical approach to identify the top influential users by using network features and contribution characteristics, which we find in existing and newly collected data set. We find that early adopter dynamics exist in the GitHub community, where early adopters have more followers in the end as expected. However, we also see counterexamples that arise due to the social networking behavior of late adopters, and due to the aging effect of older repositories and users. We publicly share the source code and the data sets for reproducing our paper.