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数据驱动的开源学术成果演化规律与合作模式分析

Translated title of the contribution: Data-driven Analysis of Evolutionary Trends and Collaboration Patterns in Open Source Academic Achievements
  • Bodian Ye
  • , Min Gao
  • , Wei Wang
  • , Yang Chen*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Open source has become a significant trend in software development, driving technological innovation and progress. Insights into current trends and collaboration models can help researchers and policymakers set reasonable goals. This paper analyzes 5990 papers related to open source from the DBLP database, published between 1998 and 2023, to explore the evolution of open-source related studies. The analysis of publication venues, titles, and citation counts reveals two main categories of research: those focused on open-source software and those on empirical studies, with the former being more prevalent. Additionally, the collaborative relationships among researchers and countries are modeled and the findings indicate that most researchers are affiliated with universities, primarily focusing on software engineering and open-source. Furthermore, collaborations tend to be concentrated within single countries, predominantly involving developed nations.

Translated title of the contributionData-driven Analysis of Evolutionary Trends and Collaboration Patterns in Open Source Academic Achievements
Original languageChinese (Traditional)
Pages (from-to)45-50
Number of pages6
JournalComputer Science
Volume52
Issue number8
DOIs
StatePublished - 15 Aug 2025

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