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.
List of analysis tools:
- Apply thesaurus
- Bigraph analysis
- Bradford Law
- Citation Analysis
- Co-word Analysis
- Collaboration Analysis
- Column Explorer
- Comparative Analysis
- Conceptual Structure
- Core Authors Analysis
- Core Sources Analysis
- Correlation Analysis
- Coverage
- Descriptive Statistics
- Extract User Keywords
- Factor Analysis
- Graph Analysis
- Growth Indicators
- Impact Analysis
- Keywords Associations
- Keywords comparison
- Latent Semantic Analysis
- Main Path Analysis
- Manage Columns
- Matrix Explorer
- Record Filtering
- Scopus Importer
- Term Analysis
- Term per year Analysis
- Text Clustering
- TF*IDF Analysis
- Thematic Analysis
- Time analysis
- Top Documents
- Worldmap
Release Information¶
Author:
Prof. Juan David Velásquez-Henao, MSc, PhDUniversidad Nacional de Colombia, Sede Medellín.Date:
February 01, 2021 Version: 0.0.0
Binary Installers:
Source Repository:
Documentation:
MIT license¶
Copyright (c) 2021 Juan David Velásquez-Henao
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.