Methods Hub - An Open Source Repository and Interactive Learning Environment for Computational Tools Enabling Network Analysis

Speaker: Chung-hong Chan

Website:

Abstract: Datasets of users’ digital behavior on social media are intrinsically relational. Computational methods are essential for analyzing the network structures in these potentially large datasets. However, many researchers, especially in the social sciences, struggle with the accessibility, usability, and applicability of these tools. On the other hand, tool developers may find it difficult to attract a large user base for their tools. This challenge of discoverability has been partially solved by online collections of tools such as Network Analysis Software Collective (NASCol, https://www.nascol.net/packages/).

As a complement to these tool collections, we present the Methods Hub, a community-driven, open-source platform that provides methods, tutorials, and interactive execution environments for analyzing digital behavioral data. The Methods Hub is tailored for social scientists, making computational methods more accessible and practical for their research. The resources on the platform cover the entire research process, from data acquisition and preprocessing to analysis, visualization, and validation. While we address different areas of application, we start with network analysis as a focus area. Our goal is to curate a collection of relevant, diverse, and high-quality content to help researchers to perform network analysis. Using these methods, researchers can, for example, calculate centrality measures, investigate information diffusion, and discover communities.

A complementary function of the Methods Hub to other tool collections is self-guided learning: it hosts step-by-step tutorials from Python and R basics to advanced topics such as dynamic network modeling and deep learning on networks. At its core are interactive execution environments that allow users to run tutorials directly in their browser. These Binder-based environments enable hands-on learning, lowering entry barriers and facilitating direct application of network analysis techniques.

Beyond learning, the Methods Hub serves as a sharing platform for computational method developers. Many tools remain underutilized due to limited dissemination. The Methods Hub provides a venue for publishing and sharing open-source tools, thereby increasing their visibility within the research community. Developers will be able to submit tools and tutorials using standardized templates, ensuring high quality, (re)usability, and computational reproducibility while minimizing submission effort.

Scheduled for public launch in mid-2025, with a prototype already released internally, the Methods Hub is a fully funded initiative to support Open Science. In particular, the combination of an inventory of tools and an interactive learning experience makes the Methods Hub truly unique among comparable online collections and repositories. Join us to see how the Methods Hub can enhance network analysis and how your network analysis tools can be hosted and widely shared among different research communities.