Analysis of Computer Science Communities Based on DBLP

TL;DR

This paper analyzes computer science communities using DBLP data, examining collaboration patterns, productivity, and stability to understand community development and compare top-ranked conferences with lower-ranked ones.

Contribution

It provides an in-depth analysis of computer science communities based on bibliometric features derived from DBLP, highlighting differences between top-ranked and lower-ranked conferences.

Findings

Top-ranked conferences have higher collaboration rates.

Community stability varies significantly across different groups.

Productivity patterns differ between communities and conference rankings.

Abstract

It is popular nowadays to bring techniques from bibliometrics and scientometrics into the world of digital libraries to analyze the collaboration patterns and explore mechanisms which underlie community development. In this paper we use the DBLP data to investigate the author's scientific career and provide an in-depth exploration of some of the computer science communities. We compare them in terms of productivity, population stability and collaboration trends.Besides we use these features to compare the sets of topranked conferences with their lower ranked counterparts.