[Paper Review] Formation of subject area and the co-authors network by sounding of Google Scholar Citations service

Dmytro Lande, Valentyna Andrushchenko|arXiv (Cornell University)|May 7, 2016

Research Data Management Practices1 references3 citations

TL;DR

This paper proposes a method for constructing subject area models and co-author networks using citation data from Google Scholar Citations. By analyzing tag-author relationships in physical optics, the approach reveals interdisciplinary collaboration patterns and enables visualization of research communities through network analysis techniques.

ABSTRACT

The suggested methodic is the way of formatting the subject areas models and co-authors networks by sounding the content networks. The paper represents the notion networks which match tags and authors of Google Scholar Citations service. Models depicted in the work were built for the physical optics area, and it can be applied for other domains. The proposed ways of defining connections between science areas and authors depicts the collaborations opportunities and versatility of interdisciplinary.

Motivation & Objective

• To develop a systematic method for modeling subject areas using citation and tagging data from Google Scholar Citations.
• To map co-author collaboration networks based on shared authorship and subject tags in scholarly publications.
• To visualize interdisciplinary connections and collaboration structures within a scientific domain.
• To demonstrate the applicability of the method beyond physical optics to other research areas.
• To provide a framework for identifying research communities and collaboration trends using open-access citation data.

Proposed method

• Utilizes citation and metadata from Google Scholar Citations to extract author-tag relationships.
• Constructs a notion network where nodes represent authors and subject tags, and edges represent co-occurrence in publications.
• Applies network analysis techniques to model connections between authors and subject areas.
• Employs visualization tools to represent the resulting co-author and subject area networks.
• Validates the model on the domain of physical optics, using real data from Google Scholar.
• Uses graph-based representations to highlight clusters of authors and thematic groupings within the subject area.

Experimental results

Research questions

• RQ1 How can subject areas be systematically modeled using citation and tagging data from Google Scholar?
• RQ2 What patterns of co-author collaboration emerge when analyzing author-tag co-occurrence networks?
• RQ3 To what extent can network visualization reveal interdisciplinary connections in scientific research?
• RQ4 How stable and representative are the resulting subject area and co-author networks in a real-world domain like physical optics?
• RQ5 Can this method be generalized to other scientific disciplines beyond physical optics?

Key findings

• The method successfully generated a coherent subject area model for physical optics using Google Scholar citation data.
• Co-author networks revealed distinct clusters of researchers, indicating strong collaborative groups within the domain.
• The analysis uncovered interdisciplinary connections between authors working on overlapping topics, even across subfields.
• Visualization of the network highlighted key authors and thematic hubs, suggesting influential contributors and emerging research trends.
• The approach demonstrated feasibility and reproducibility in mapping research communities using publicly available citation data.
• The resulting models can be extended to other domains, offering a scalable framework for research landscape analysis.