litstudy 0.2.0

Using the power of Python and Jupyter notebooks to automate analysis of scientific literature

litstudy

litstudy is a Python package that allows analysis of scientific literature from the comfort of a Jypyter notebook. It enables selecting scientific publications and study their metadata using visualizations, network analysis, and natural language processing.

In essense, this package offers five features

• Extract metadata of scientific documents from various sources. The data is unitied by a standard interface, allowing data from different sources to be combined.
• Filter, select, dudplibcate, and annotate collections of documents.
• Compute and plot general statistics of document sets (e.g., statistics on authors, venues, publication years, etc.)
• Generate and plot various bibliographic networks as an interactive visualization.
• Topic discovery based on natural language processing (NLP) allows automatic discovery of popular topics.

Documentation

Document is available here.

Requirements

The package has been tested for Python 3.6. Required packages are available in requirements.txt.

To access the Scopus API using litstudy, you (or your institute) needs a Scopus subscription and you need to request an Elsevier Developer API key (see Elsevier Developers.

Example

An example notebook is available in notebooks/example.ipynb and here.

Running using virtualenv

Installation using virtualenv is can be using the following commands:

Create virtualenv environment named myenv:

virtualenv myenv --python=`which python3`

Activate virtual environment

source ./myenv/bin/activate

Install requirement dependencies.

pip3 install -r requirements.txt

Install new Jupyter kernel.

ipython kernel install --user --name=myenv

Run Jupyter and select myenv as kernel. Remaining instructions can be found within the notebook itself.

jupyter notebook --MappingKernelManager.default_kernel_name=myenv

License

Apache 2.0. See LICENSE.

Change log

See CHANGELOG.md.

Contributing

See CONTRIBUTING.md.

Related work

Don't forget to check out these amazing software packages!

• ScientoPy: Open-source Python based scientometric analysis tool.
• pybliometrics: API-Wrapper to access Scopus.
• metaknowledge: Python library for doing bibliometric and network analysis in science.
• tethne: Python module for bibliographic network analysis.
• VOSviewer: Software tool for constructing and visualizing bibliometric networks.