In our research, we address various issues pertaining to the broader topic of data science. We are particularly interested in the development of methods for the study of large relational datasets, complex systems analysis, and collections of time-stamped interactions from various disciplines.

The methods highlighted here range from network science tools, data scraping and inference, and disambiguation.

Related Publications

Empirical Networks are Sparse: Enhancing Multi-Edge Models with Zero-Inflation

arXiv Preprint - 2024

Giona Casiraghi and Georges Andres

Disentangling the Timescales of a Complex System: A Bayesian Approach to Temporal Network Analysis

ArXiv Preprint - 2024

Giona Casiraghi and Georges Andres

Reconstructing signed relations from interaction data

Scientific Reports - 2023

Georges Andres, Giona Casiraghi, Giacomo Vaccario and Frank Schweitzer

Predicting variable-length paths in networked systems using multi-order generative models.

Applied Network Science - 2023

Christoph Gote, Giona Casiraghi, Frank Schweitzer and Ingo Scholtes

Detecting and Optimising Team Interactions in Software Development

arXiv - 2023

Christian Zingg, Alexander von Gernler, Carsten Arzig, Frank Schweitzer and Christoph Gote

Locating Community Smells in Software Development Processes Using Higher-Order Network Centralities

Social Network Analysis and Mining - 2023

Christoph Gote, Vincenzo Perri, Christian Zingg, Giona Casiraghi, Carsten Arzig, Alexander von Gernler, Frank Schweitzer and Ingo Scholtes

Big Data = Big Insights? Operationalising Brooks' Law in a Massive GitHub Data Set

2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE) - 2022

Christoph Gote, Pavlin Mavrodiev, Frank Schweitzer and Ingo Scholtes

A network approach to expertise retrieval based on path similarity and credit allocation

Journal of Economic Interaction and Coordination - 2021

Xiancheng Li, Luca Verginer, Massimo Riccaboni and P. Panzarasa

gambit - An Open Source Name Disambiguation Tool for Version Control Systems

2021 IEEE/ACM 18th International Conference on Mining Software Repositories (MSR) - 2021

Christoph Gote and Christian Zingg

The likelihood-ratio test for multi-edge network models

J. Phys. Complex. 2 035012 - 2021

Giona Casiraghi

HYPA: Efficient Detection of Path Anomalies in Time Series Data on Networks

Proceedings of the 2020 SIAM International Conference on Data Mining - 2020

Timothy LaRock, Vahan Nanumyan, Ingo Scholtes, Giona Casiraghi, Tina Eliassi - Rad and Frank Schweitzer

A Gaussian Process-based Self-Organizing Incremental Neural Network

2019 International Joint Conference on Neural Networks (IJCNN) - 2019

X. Wang, Giona Casiraghi, Yan Zhang and J. Imura

Quantifying Triadic Closure in Multi-Edge Social Networks

ACM - 2019

Laurence Brandenberger, Giona Casiraghi, Vahan Nanumyan and Frank Schweitzer

git2net - An Open Source Package to Mine Time-Stamped Collaboration Networks from Large git Repositories

Proceedings of the 16th International Conference on Mining Software Repositories - 2019

Christoph Gote, Ingo Scholtes and Frank Schweitzer

From Relational Data to Graphs: Inferring Significant Links Using Generalized Hypergeometric Ensembles

Social Informatics: 9th International Conference, SocInfo 2017, Oxford, UK, September 13-15, 2017, Proceedings, Part II - 2017

Giona Casiraghi, Vahan Nanumyan, Ingo Scholtes and Frank Schweitzer

Multiplex Network Regression: How do relations drive interactions?

arXiv e-print - 2017

Giona Casiraghi