iNaturalist citizen science community during City Nature Challenge: new computational approach for analysis of user activity

TL;DR

This paper introduces a computational approach to analyze user activity patterns in the iNaturalist citizen science community during the City Nature Challenge, revealing insights into user behavior and interactions over time.

Contribution

It presents novel statistical and network science methods for exploring the spatio-temporal evolution and user interaction dynamics in citizen science communities.

Findings

Significant differences in user engagement levels.

Distinct user roles and interaction patterns identified.

Insights applicable to other citizen science projects.

Abstract

Analysing patterns of engagement among citizen science participants can provide important insights into the organisation and practice of individual citizen science projects. In particular, methods from statistics and network science can be used to understand different types of user behaviour and user interactions to help the further implementation and organization of community efforts. Using publicly available data from the iNaturalist community and their yearly City Nature Challenges (CNC) from 2017-2020 as an example; we showcase computational methods to explore the spatio-temporal evolution of this citizen science community that typically interacts in a hybrid offline-online way. In particular, we investigate the user types present in the community along with their interactions, finding significant differences in usage-behavior on both the level of engagement and the types of community tasks/roles and how they interact with the network of contributors. We expect that these computational analysis strategies will be useful to gain further understanding of other citizen science communities and projects.