Technologies

Technologies do not emerge in isolation. They grow through connections between ideas, tools, firms, skills and communities. This research stream maps these links to understand how technologies evolve and where new technological potential appears.

We study technology as a space of related possibilities. Using network science, natural language processing and large-scale digital trace data, we examine how digital technologies are combined, adopted and replaced across platforms, industries and places. Our work covers areas such as machine learning, programming technologies, general-purpose AI and industry-level digital transformation.

By revealing the structure of the technology space, we aim to identify early signals of change. These signals help us understand which technologies are gaining relevance, which capabilities they build on, and where they may open new paths for startups, innovation and work.

Goals

  1. Map how technologies connect, evolve and diffuse.
  2. Identify early signals of technological potential.
  3. Understand how firms, communities and places turn technologies into innovation.

From Borchers C, Braesemann F. 2025 The innovation dynamics of programming technologies

programming language networks

Publications

Code Review

Global networks in collaborative programming

By Fabian Braesemann, Niklas Stoehr and Mark Graham

Knowledge exchange between programmers is theoretically geographically unrestricted but it strongly clusters in metropolitan regions in North America, Western Europe, and South Asia.

Science of Startups Initiative
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