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Related Experiment Video

Updated: Nov 1, 2025

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

Published on: August 18, 2023

Community evolution on Stack Overflow.

Iraklis Moutidis¹, Hywel T P Williams^1,2

¹Computer Science, University of Exeter, Exeter, United Kingdom.

|June 17, 2021

Summary

This summary is machine-generated.

Stack Overflow data reveals persistent web development communities and limited user mobility. Analysis of user-technology interactions shows evolving programming language popularity over time.

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Area of Science:

Computer Science
Social Computing
Data Science

Background:

Stack Overflow is a major Q&A platform for developers, facilitating knowledge sharing since 2008.
Community moderation via voting shapes content quality and user engagement.
The platform hosts a vast repository of crowd-sourced software development knowledge.

Purpose of the Study:

To analyze Stack Overflow data (2008-2020) to identify trends in technology groupings and user sub-communities.
To examine the evolution and interconnection of these user-technology communities over time.
To understand the dynamics of user behavior and technology adoption within the developer community.

Main Methods:

Analysis of all questions, answers, votes, and tags from Stack Overflow (2008-2020).
Generation of user-technology interaction graphs.
Application of community detection algorithms to identify and track user communities annually.

Main Results:

Web development consistently formed the largest and most persistent user communities.
Users generally exhibit low mobility between communities, either staying within one or gaining no score.
Community evolution highlights shifts in the popularity of programming languages and frameworks on Stack Overflow.

Conclusions:

Stack Overflow data provides valuable insights into developer community structures and dynamics.
Long-term trends in the software development industry are reflected in user-technology interactions.
The study identifies stable community structures and evolving technology preferences among developers.