Visualizing citation network for research evaluation
Research evaluation measures research quality in several dimensions, such as research projects, researchers, institutions, research output and impact, and more.
Research evaluation measures research quality in several dimensions, such as research projects, researchers, institutions, research output and impact, and more.
VOSviewer is a popular software that visualizes connections between research works. You can use it to create networks of term co-occurrence. Here is a very good training video that guides you to do that.
With Connected papers, you can explore papers in your research field using graphs. You may discover more papers than traditional literature searches.
In your academic writing, you may cite a work to support your findings, or you may cite to refute the argument in the cited work. Citation count ("1" in both cases) does not tell you how a work is cited. Now there are tools that can reveal citation contexts. This post introduces one of such tools: scite.
Why does Google Scholar show higher citation counts than Scopus and Web of Science? What tools are better for tracing citations in fields outside of science and engineering?
You are probably familiar with using Scopus, Web of Science, and Google Scholar to find citations between scholarly works. This week, we look at alternative citation indices that are also powerful, and free to use!
A smart city uses innovation and technology to address urban challenges, improve the effectiveness of public services, make the city more liveable and sustainable. To achieve these, open data is an essential foundation.
As a researcher, sometimes you may need to share your data to meet publishers’ or funders’ requirement, but the process of preparing your data can be tedious and time-consuming. In this regard, DataSpace@HKUST can help.
Library Research Support Services recently did a small-scale study to learn about the text and data mining (TDM) policies of some of our databases. We found that most of them allow TDM under certain conditions.
In August 2020, arXiv announced its entire corpus consisting 1.7 million scholarly articles is available as a free dataset on Kaggle.