What defines and influences replicability in computational communication science?

Description of the project

This project investigates the factors that influence the potential replicability of Computational Communication Science (CCS) and how these factors affect the actual replicability of scientific studies. The spread of digital technologies has led to a wealth of digital trace data, which presents new methodological opportunities and challenges, especially for communication science. Digital data processing allows for the analysis of data in previously unattainable breadth, depth, and scale. However, despite growing support for open science principles, numerous challenges remain that hinder the replicability of studies. These include legal and ethical issues regarding copyright and data privacy, dependence on third parties for data use, and technological barriers to reusing research resources such as software and code.

The project aims to systematically investigate these challenges and identify replicability potentials. Initially, the potential replicability of studies in CCS was assessed through a large-scale content analysis of publications. Subsequently, selected studies were reproduced and replicated to test and evaluate the practical relevance of the identified challenges. The focus is on the methodological diversity of CCS, the volatility of the research subjects examined—such as news content or social media posts—and the increasing dependence on platform providers.

With the aim of understanding the mechanisms that determine the success or failure of replications, the project makes an important contribution to promoting a transparent and replicable scientific culture. It thus plays a significant role in strengthening the credibility, value, and usefulness of science in a sustainable way.

This project represents the first phase of the RepCCS project.

Keywords

Open Science | Replicability | Computational Communication Science

External partners

• Dr. Johannes Breuer