Exploring the social influence of Kaggle virtual community on the M5 competition

TL;DR

This paper investigates how the Kaggle virtual community influenced participant behaviors in the M5 forecasting competition through content analysis and social network examination.

Contribution

It provides new insights into the social dynamics and influence mechanisms within online data science communities during competitions.

Findings

Identification of key topics and trends in the community

Mapping of the virtual community's relationship network

Characterization of influential participants and their roles

Abstract

One of the most significant differences of M5 over previous forecasting competitions is that it was held on Kaggle, an online platform of data scientists and machine learning practitioners. Kaggle provides a gathering place, or virtual community, for web users who are interested in the M5 competition. Users can share code, models, features, loss functions, etc. through online notebooks and discussion forums. This paper aims to study the social influence of virtual community on user behaviors in the M5 competition. We first research the content of the M5 virtual community by topic modeling and trend analysis. Further, we perform social media analysis to identify the potential relationship network of the virtual community. We study the roles and characteristics of some key participants that promote the diffusion of information within the M5 virtual community. Overall, this study provides in-depth insights into the mechanism of the virtual community's influence on the participants and has potential implications for future online competitions.