MetaInfoSci: An Integrated Web Tool for Scholarly Data Analysis

TL;DR

MetaInfoSci is a comprehensive web platform that unifies bibliometric, scientometric, and network analysis tools, enabling researchers to perform integrated, customizable, and AI-assisted scholarly data analysis across multiple sources.

Contribution

It introduces MetaInfoSci, the first platform to combine diverse bibliometric and network analysis features with AI-driven summaries in a single, user-friendly web interface.

Findings

Supports tailored queries and cross-database data merging.

Provides rich, customizable visualizations.

Offers automated AI-generated summaries of results.

Abstract

The exponential increase in academic publications has made it increasingly difficult for researchers to remain up to date and systematically synthesize knowledge scattered across vast and fragmented research domains. Literature reviews, particularly those supported by bibliometric methods, have become essential in organizing prior findings and guiding future research directions. While numerous tools exist for bibliometric analysis and network science, there is currently no single platform that integrates the full range of features from both domains. Researchers are often required to navigate multiple software environments, many of which lack customizable visualizations, cross-database integration, and AI-assisted result summarization. Addressing these limitations, this study introduces MetaInfoSci at www.metainfosci.com, a comprehensive, web-based platform designed to unify bibliometric, scientometric, and network analytical capabilities. The platform supports tailored query design, merges data from diverse sources, enables rich and adaptable visual outputs, and provides automated, AI-driven summaries of analytical results. This integrated approach aims to enhance the accessibility, efficiency, and depth of scientific literature analysis for scholars across disciplines.