AI-Generated Tools for Academic Research

How it Works:

• Uses a similarity metric combining: (a) Co-citations (two documents cited together by others) and (b) Bibliographic coupling (two works referencing a common third work)
• Leverages the Semantic Scholar corpus:
  • A free, AI-powered research tool
  • Provides a comprehensive database of academic papers
  • Utilizes machine learning techniques

User Interaction:

• Discover relevant papers by: a) Starting with one or more seed papers or b) Searching for keywords
• Filter papers by publication year, keyword, PDF availability, or open access
• Use list view to see percentage of similarity to origin paper
• Use prior works to show seminal, most frequently cited papers
• Use derivative works for recent papers

Visual Representation:

• Generates a Force Directed Graph:
  • Each node represents a paper
  • Line length on map shows degree of connectedness
  • Size of the node represents number of citations
  • Darker color represents more recent publications
• Clusters similar papers together (force-directed layout algorithm simulates attractive and repulsive forces between the nodes)

Notable Features:

• Integrates with Zotero

Benefits:

• Easy identification of key research areas
• Highlights seminal works in the field

Limitations:

• Freemium model
  • Free version only allows for 2 graphs, then requires user account for up to 5 graphs per month
  • $6/month for academic subscription
• Limited to English
• Visual interface may challenge some users
• Possible blind spots, such as underrepresented researchers, niche topics, articles behind a paywall, or very recent papers that aren't cited yet