There are 6 repositories under citation-network topic.
Retrieve author and publication information from Google Scholar in a friendly, Pythonic way without having to worry about CAPTCHAs!
An R-tool for comprehensive science mapping analysis. A package for quantitative research in scientometrics and bibliometrics.
This web app aims to help scientists with their literature review using metadata from OpenAlex (OA), Semantic Scholar (S2) and Crossref (CR) in local citation networks.
GraphTranslator:Aligning Graph Model to Large Language Model for Open-ended Tasks
SYNERGY - Open machine learning dataset on study selection in systematic reviews
Measuring the Evolution of a Scientific Field through Citation Frames
Tools, datasets, Corpus and Venue Challenge for scholarly big data——Pick up scattered pearls
This repository contains the official implementation for the AAAI25 paper "From Words to Worth: Newborn Article Impact Prediction with LLM".
Scimeetr is an R package, and a shiny app that helps researchers introduce themselves into their scholarly literature. It contains a suit of function that let someone: load bibliometric data into R, make a map of peer reviewed papers by creating various networks, find research community, characterize the research communities, and generate reading list.
Asclepias broker
Graph that downloads patent citation data from USPTO's PatentsView API on-demand and stores it locally in an SQL database (and in memory) for fast access later.
This package contains the dataset named named "Large-scale Multi-layer Academic Networks (LMANStat)" and the code in Gao, Zhang, Pan, and Wang's paper titled "Large-scale Multi-layer Academic Networks Derived from Statistical Publications".
A command line tool for querying and modeling citation networks from the Astrophysical Data System (ADS) in a format compatible with Gephi
Citation network analysis using OpenAlex and 3d-force-graph
The Academic Review Tool (ART) is a package for performing academic reviews and bibliometric analyses in Python. It offers capabilities for discovering, retrieving, and analysing academic literature at scale.
:stars: Analysis of Microsoft Academic Research Database using Hadoop.
A graph-based citation network for paper recommender engine
Find the citation network from patent data collected from 1976 to 2006.
A bird's-eye view of patent landscape.
ISI 7th Summer School Project on implementing 2-layer GCN on CORA, CiteSeer, PubMed datasets, using PyTorch, and analyzing Oversmoothing by going deep upto 1024 layers
Visualize citations and references of a source publication in 3D.
Graph Analysis of citations among DCU researchers using GraphX (Apache Spark).
Creates a citation network from biblatex or bibtex reference file and visualises the references between them. Uses the open citation API.
Citation Provenance
Link prediction is the problem of predicting the existence of a link between two entities in a network. The goal of this kaggle challenge was to predict whether two nodes are linked by an edge or not
💤 A computational study on sleeping beauties discovery in case law.
DoConA (Document Content and Citation Analysis Pipeline) is an open source, configurable and extensible Python tool to analyse the level of agreement between the citation network of a set of textual documents and the textual similarity of these documents.
Aim is to convert nodes and node attributes of the DBLP Citation graph to analyze graph specific trends. This objective entailed two tasks, recreating a search algorithm for sampling the neighborhood as per the Node2Vec algorithm and extract feature embeddings using the Word2Vec skip-gram architecture. The nodes (papers)are represented into a fixed size multi-space dimension that is capable of capturing closeness of two papers based on a mentioned metric. The final classification of groups is based on the feature embeddings, performed by the spectral clustering algorithm. The sense-making converts to a search based optimization problem as we built our model to maximize the probability of each node belonging to a neighborhood found depending on the likelihood of revisiting a node and of out-ward exploration.
The purpose of this project is to construct a ranking metric to evaluate academic papers and researchers using available data in citation network dataset.
A set of methods and model evaluation metrics for predicting links in an academic citation network using Apache Spark and Scala
A project using Graph Neural Networks (GNNs) to classify nodes in the Cora citation network. Implements GCN and GraphSAGE models using PyTorch Geometric to classify academic papers based on citation relationships. Includes preprocessing, model training, evaluation, and visualizations.