Analysis of bibliographic datasets using Python

TechMiner is a package for mining relevant information about topics related to Research and Development (R&D) literature extracted from bibliographical databases as Scopus. TechMiner facilitates studies of systematic mapping of literature and Tech mining studies. The package can be used by users with basic knowledge of Python programming. However, users with advanced knowledge in programming and text mining can easily incorporate their codes to maximize the power of the library and develop advanced analysis. The package can be used to:

• Realize analyzes based on document-by-term pattern, for example, number of documents by author, by source or by keyword.

• Calculate and plot the number of documents or citations by year.

• Realize analyzes based on term-by-term pattern, for example, number of documents by keywords and by author, by keyword and by year and so on.

• Compute and plot co-ocurrence, correlation and autocorrelation matrices.

• Realize Principal Component Analysis to detect and analyze clusters of data.

• Plot heatmaps, networks and many other types of plots for analyzing data.

TechMiner is an open source (distributed under the MIT license) and friendly-user package developed and tested in Python version 3.6.

TechMiner runs on top of Jupyter Lab and Google Colaboratory with its own graphical user interfase. This feature allows to new user to run TechMiner easily. This is particulary benefical because of the large number of analysis functions that the tool has. Due to the design of the package, it is easy to use techMiner with the tools available in the ecosystem of open source tools.

Getting Started

The current stable version can be installed from the command line using:

$ pip install techminer

The current development version can be installed by clonning the GitHub repo https://github.com/jdvelasq/techminer and executing

$ python3 setup.py install develop

at the command prompt.

To run the TechMiner GUI, the user must execute

    from techminer.app import App

    App().run()

in a cell of Jupiter Lab or Google Colaboratory.

Release Information

• Author:

  Prof. Juan David Velásquez-Henao, MSc, PhD Universidad Nacional de Colombia, Sede Medellín. jdvelasq@unal.edu.co

• Date:

  February 01, 2021 Version: 0.1.0

• Binary Installers:

  https://pypi.org/project/techminer

• Source Repository:

  https://github.com/jdvelasq/techminer

• Documentation:

  https://jdvelasq.github.io/techminer/