There is an increasing interest in research that utilizes digital trace data. Information systems, among other fields, has claimed to take a leading role in this emerging research genre. While there are single research papers on specific aspects of digital trace data research, such as data quality or the application of a particular method, there is currently no book that treats the different stages of a research project that is based on digital trace data.


This book aims to address this gap and will treat the research process of studies that use digital trace data in an end-to-end fashion, i.e. from the point that data has been extracted up to the point of deriving theoretical insights that can be published in the top journals of our field. With this book, we intend to provide an authoritative source that students and established scholars can turn to in order to understand the different aspects that are important for research with digital trace data. The book discusses foundations of digital trace data research, different methods to analyze digital trace data, and points to prototypical studies that draw on digital trace data to investigate different organizational phenomena.


While the book aims to specifically address the particularities of digital trace data research in information systems, we also encourage submissions from neighboring fields, such as computer science, management science, and organization studies.


Submissions can address, but are not limited to, the following topics:


Foundations of digital trace data research: Data quality and data usage in the research process

-Research opportunities and challenges of digital trace data research

-How to organize digital trace data research projects

-Data quality and ethics

-Developing theory using digital trace data

-Testing theory using digital trace data

-Integrating human and machine pattern recognition


Methods for digital trace data analysis

-Visual analytics and interactive data analysis

-Text mining

-Social/dynamic network analysis

-Social sequence analysis

-Machine learning


Applications of digital trace data research in information systems and related fields of study

-Open-source software development

-Process/ routines research in IS

-Communication in social networks (twitter, etc.)