The number of scientific publications continues to rise exponentially,
especially in Computer Science (CS). However, current solutions to analyze
those publications restrict access behind a paywall, offer no features for
visual analysis, limit access to their data, only focus on niches or
sub-fields, and/or are not flexible and modular enough to be transferred to
other datasets. In this thesis, we conduct a scientometric analysis to uncover
the implicit patterns hidden in CS metadata and to determine the state of CS
research. Specifically, we investigate trends of the quantity, impact, and
topics for authors, venues, document types (conferences vs. journals), and
fields of study (compared to, e.g., medicine). To achieve this we introduce the
CS-Insights system, an interactive web application to analyze CS publications
with various dashboards, filters, and visualizations. The data underlying this
system is the DBLP Discovery Dataset (D3), which contains metadata from 5
million CS publications. Both D3 and CS-Insights are open-access, and
CS-Insights can be easily adapted to other datasets in the future. The most
interesting findings of our scientometric analysis include that i) there has
been a stark increase in publications, authors, and venues in the last two
decades, ii) many authors only recently joined the field, iii) the most cited
authors and venues focus on computer vision and pattern recognition, while the
most productive prefer engineering-related topics, iv) the preference of
researchers to publish in conferences over journals dwindles, v) on average,
journal articles receive twice as many citations compared to conference papers,
but the contrast is much smaller for the most cited conferences and journals,
and vi) journals also get more citations in all other investigated fields of
study, while only CS and engineering publish more in conferences than journals.

本论文使用计量学方法分析计算机科学的元数据，并使用交互式 Web 应用程序 CS-Insights 进行数据可视化，发现了计算机科学领域在过去两十年中出现了大量新的作者和出版物，会议论文的受欢迎程度下降，期刊文章的引用次数更高。

使用 DBLP Discovery 数据集分析计算机科学研究的现状

Analyzing the State of Computer Science Research with the DBLP Discovery Dataset

This paper presents CS-Insights, an interactive web application to analyze
computer science publications from DBLP through multiple perspectives. The
dedicated interfaces allow its users to identify trends in research activity,
productivity, accessibility, author's productivity, venues' statistics, topics
of interest, and the impact of computer science research on other fields.
CS-Insightsis publicly available, and its modular architecture can be easily
adapted to domains other than computer science.

CS-Insights 是一款交互式网络应用程序，可通过多个角度分析 DBLP 中的计算机科学出版物，用户可以通过专用的界面识别研究活动趋势、作者和会议的统计数据、感兴趣的话题以及计算机科学研究对其他领域的影响。CS-Insights 是公开的，其模块化架构可以轻松地适应于计算机科学以外的领域。