This program somehow creates a network of article references and provides a connection between authors and keywords, these things are usually called "Citation Graph".
Following are similar cases:
Providing a reliable source of scholarly data for developers This index over 200 million academic papers sourced from publisher partnerships, data providers, and web crawls.
https://www.semanticscholar.org/product/api
created a tool for you homo academicus to automatically create the said citation graph for any paper. This should be helpful for researchers to catch up on the trend of a rapidly changing field.
First, if you are using Mendeley (or any other Reference Management Software), export your papers as a .bib file which should include the arXiv ID and issue year information. Then, use Mathematica to run the code. It will take you to the Astrophysics Data System of Harvard and find out the list of reference for each paper. Finally, a citation graph will be drawn with the help of Wolfram Language.
https://community.wolfram.com/groups/-/m/t/1770600
https://lanstonchu.wordpress.com/2019/08/20/automatic-generation-of-academic-citation-graph/
https://github.com/lanstonchu/citation-graph
The ADS maintains three bibliographic collections containing more than 15 million records covering publications in astronomy and astrophysics, physics, and general science, including all arXiv e-prints. Abstracts and full-text of major astronomy and physics publications are indexed and searchable through the new ADS modern search form as well as a classic search form. A browsable paper form is also available.
https://ui.adsabs.harvard.edu/
Connected Papers is a unique, visual tool to help researchers and applied scientists find and explore papers relevant to their field of work.
To create each graph, we analyze an order of ~50,000 papers and select the few dozen with the strongest connections to the origin paper.
Our database is connected to the Semantic Scholar Paper Corpus (licensed under ODC-BY). Their team has done an amazing job of compiling hundreds of millions of published papers across many scientific fields.
https://www.connectedpapers.com/
A citation graph (or citation network), in information science and bibliometrics, is a directed graph that describes the citations within a collection of documents. Each vertex (or node) in the graph represents a document in the collection, and each edge is directed from one document toward another that it cites (or vice versa depending on the specific implementation).
https://dbpedia.org/page/Citation_graph
It’s like a second brain to do literature review! It does half the work for you… and makes life a lot easier!
https://www.researchrabbit.ai/
https://networkrepository.com/cit.php
Creating an Open Citation Graph from PDF Documents
https://www.ipvs.uni-stuttgart.de/news/news/Creating-an-Open-Citation-Graph-from-PDF-Documents/
OpenCitations is an independent not-for-profit infrastructure organization for open scholarship dedicated to the publication of open bibliographic and citation data by the use of Semantic Web (Linked Data) technologies.
OpenAlex is a free and open catalog of the global research system. It's named after the ancient Library of Alexandria and made by the nonprofit OurResearch.
This is the help center for OpenAlex, containing information about the data, the website where you can start exploring, and the background concepts. To learn about the API, the data snapshot, and other fun stuff, head over to our technical documentation.
At the heart of OpenAlex is our dataset—a catalog of works. A work is any sort of scholarly output. A research article is one kind of work, but there are others such as datasets, books, and dissertations. We keep track of these works—their titles (and abstracts and full text in many cases), when they were created, etc. But that's not all we do. We also keep track of the connections between these works, finding associations through things like journals, authors, institutional affiliations, citations, concepts, and funders. There are hundreds of millions of works out there, and tens of thousands more being created every day, so it's important that we have these relationships to help us make sense of research at a large scale.
This type of data is a valuable resource to institutions, researchers, governments, publishers, funders, and anyone else interested in global research and scholarly communication. We offer the data freely so that its value can be shared. Using the website, anyone can get started right away exploring the data to learn about all sorts of things, from individual papers, to global research trends.
OurResearch is a nonprofit that builds tools for Open Science, including OpenAlex, Unpaywall, and Unsub, among others. Our open-source tools are used by millions every day, in universities, businesses, and libraries worldwide, to uncover, connect, and analyze research products.
Openness is one of our core values, and so we strive to bake it into everything we do—including our data, code, software, and organizational practices. This is also why OpenAlex is completely open-source and free to use under the CC0 license.
OpenAlex offers an open replacement for industry-standard scientific knowledge bases like Elsevier's Scopus and Clarivate's Web of Science. Compared to these paywalled services, OpenAlex offers significant advantages in terms of inclusivity, affordability, and availability.
https://help.openalex.org/hc/en-us
pyBibX - A Python Library for Bibliometric and Scientometric Analysis Powered withArtificial Intelligence Tools
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.
PyblioNet is a software tool for the creation, visualization and analysis of bibliometric networks based on Pybliometrics, NetworkX and VisJs. It combines a Python-based data collection tool that accesses the Scopus database with a browser-based visualization and analysis tool. It allows users to create networks of publication data based on citations, co-citations, shared authors, bibliographic coupling, and shared keywords.
Article PyblioNet – Software for the creation, visualization and analysis of bibliometric networks
A Python library for doing bibliometric and network analysis in science and health policy research
https://github.com/UWNETLAB/metaknowledge
Tethne provides tools for easily parsing and analyzing bibliographic data in Python. The primary emphasis is on working with data from the ISI Web of Science database, and providing efficient methods for modeling and analyzing citation-based networks. Future versions will include support for PubMed, Scopus, and other databases.
As of v0.3, Tethne is beginning to include methods for incorporating data from the JSTOR Data-for-Research service, and MALLET topic modeling.
https://pythonhosted.org/tethne/index.html
https://github.com/diging/tethne
A Python Parser for PubMed Open-Access XML Subset and MEDLINE XML Dataset
https://github.com/titipata/pubmed_parser
open-source web-based search and metadata organization of scientific literature
https://pubmed.ncbi.nlm.nih.gov/30678631/
https://github.com/NeuroMorphoOrg/PaperBot
Paperfetcher: A tool to automate handsearching and citation searching for systematic reviews
https://onlinelibrary.wiley.com/doi/epdf/10.1002/jrsm.1604
https://paperfetcher.github.io/
https://github.com/paperfetcher/paperfetcher-web-app
https://github.com/paperfetcher/paperfetcher
Since v0.2.4 paperscraper also supports scraping PDF files directly! Thanks to @daenuprobst for suggestions!
https://github.com/PhosphorylatedRabbits/paperscraper
https://www.sciencedirect.com/science/article/abs/pii/S1751157717300500
https://www.bibliometrix.org/home/
Numerous software tools support bibliometric analysis; however, many of these do not assist scholars in a complete recommended workflow. The most relevant tools are CitNetExplorer (van Eck & Waltman, 2014), VOSviewer (van Eck & Waltman, 2010), SciMAT (Cobo, López-Herrera, Herrera-Viedma, & Herrera, 2012), BibExcel (Persson, Danell, & Schneider, 2009), Science of Science (Sci2) Tool (Sci2 Team, 2009), CiteSpace (Chen, 2006), and VantagePoint (www.thevantagepoint.com).
The Science of Science (Sci2) Tool is a modular toolset specifically designed for the study of science. It supports the temporal, geospatial, topical, and network analysis and visualization of scholarly datasets at the micro (individual), meso (local), and macro (global) levels.
https://sci2.cns.iu.edu/user/index.php
https://github.com/CIShell/sci2
https://github.com/CIShell/sci2-docker-vnc
Tools to visualize connections between academic publications
https://proto-knowledge.blogspot.com/2015/02/tools-to-visualize-connections-between.html