Abstract

In this paper, we constructed a system dynamic model of Wikipedia based on the co-evolution theory, and investigated the interrelationships among topic popularity, group size, collaborative conflict, coordination mechanism, and information quality by using the vector error correction model (VECM). This study provides a useful framework for analyzing the dynamics of Wikipedia and presents a formal exposition of the VECM methodology in the information system research.

Highlights

  • Wikipedia has become one of the most striking emblems of mass collaboration

  • As an attempt complementary to the previous studies, this study constructs the PSCCQ model, a system model consisting of five microcosmic factors, with which we explore the fundamental dynamic mechanism behind Wikipedia

  • We have systematically investigated the dynamic interrelationships among topic popularity, group size, collaborative conflict, coordination mechanism, and information quality in Wikipedia through a detailed empirical analysis

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Summary

Introduction

Wikipedia has become one of the most striking emblems of mass collaboration. Its unprecedented success has posed challenges to traditional theories of public goods and collective-action, which has inspired many scholars from various fields to study it [1, 2]. Existing research highlights many factors that are crucial to the success of Wikipedia, including topic popularity, group size, collaborative conflict, coordination mechanism, and information quality, etc [3]. Most of these studies examine the relationships among factors from a static perspective without considering the dynamic evolution of Wikipedia. Based on the co-evolution theory, we build the PSCCQ model as a theoretical framework to analyze the dynamic interactions among topic popularity, group size, collaborative conflict, coordination mechanism, and information quality, and reveal the dynamics of Wikipedia (cf Fig. 1).

Research context
Data collection
Granger causality tests
Impulse response functions
Forecast error variance decomposition
Findings
Discussion
Full Text
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