How to Build a Citation Graph for Academic Paper Networks

Academic citations form a rich network that reveals research influence and knowledge flow. Here's how to scrape citation data and build a citation graph for academic analysis. Why Build a Citation Graph? Citation networks help identify seminal papers, discover research clusters, track idea propagation, and find under-cited work that deserves attention. Setup import requests import networkx as nx import pandas as pd from collections import deque import time Using Semantic Scholar API def get_paper_details ( paper_id ): url = f " https://api.semanticscholar.org/graph/v1/paper/ { paper_id } " params = { " fields " : " title,authors,year,citationCount,references.title,references.paperId,citations.title,citations.paperId " } resp = requests . get ( url , params = params , timeout = 15 ) return resp . json () if resp . status_code == 200 else None def search_papers ( query , limit = 20 ): url = " https://api.semanticscholar.org/graph/v1/paper/search " params = { " query " : query , " limit "