Executive Summary & Overview

Automated bibliometric & NLP analysis of Mendeley BibTeX metadata (Abuella, 2024 methodology)
Dataset: None (Upload .bib)
Total BibTeX Entries
0
Upload .bib to analyze
Publication Year Span
—
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Dominant Document Type
—
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Top Theme / Mendeley Tag
—
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Methodology & Automated Analysis Pipeline (Abuella, 2024)

This interactive dashboard implements the end-to-end automated academic literature review workflow described in "Automating Academic Document Analysis with ChatGPT: A Mendeley Case" (Mohamed Abuella, 2024). Directly inside your browser, it parses standard Mendeley-exported .bib files, extracts structured bibliometric fields (title, abstract, author, year, journal, mendeley-tags, keywords), computes TF-IDF weighted n-gram vectors, clusters documents into latent research themes, and renders publication-grade figures and tables with high-DPI PNG, vector PDF, and plain-text TXT exports.

Stage 1
BibTeX Ingestion
Parses @article, @techreport, @misc, @book, @inproceedings, braces & LaTeX accents.
Stage 2
NLP Text Cleaning
Tokenizes title + abstract, strips academic stopwords, normalizes domain terms.
Stage 3
Bibliometric Profiling
Computes yearly growth, venue concentration, author productivity, and Mendeley tag frequencies.
Stage 4
Word Clouds & Topics
Generates high-density Title/Abstract word clouds and 6-cluster TF-IDF cosine topic assignments.
Stage 5
Interactive Export
Zoomable canvases & tables with instant ⬇️ PNG, ⬇️ PDF, ⬇️ TXT, and ⬇️ CSV downloads.
☁️ Featured Overview Figure: Title & Abstract Word Cloud (Combined Text Context)
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Overview Word Cloud: Most prominent terms extracted from combined title and abstract text across all entries in the active .bib collection (weighted by TF-IDF & corpus frequency).
📋 Executive Summary Table: Collection Composition & Research Themes
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Research Cluster / Category Doc Count Share (%) Year Range Top Characteristic Terms (Title & Abstract) Representative Mendeley Tags
Summary Table: High-level thematic synthesis of the active Mendeley BibTeX corpus grouped by discovered research clusters.

Title & Abstract Text Context Word Cloud Generator

Customize the text source, maximum word count, and academic color palette below. The word cloud dynamically computes term weights from the active .bib collection.

☁️ High-Resolution Corpus Word Cloud
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Word cloud generated from combined title and abstract text across all documents in the collection. Font size reflects weighted corpus prominence.

Temporal Publication Distribution (Replicating Abuella, 2024)

📈 Publications per Year
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Number of academic publications per year in the active Mendeley BibTeX collection, illustrating recent research acceleration.
🧭 2D Semantic Document-Topic Map
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2D semantic projection of documents based on TF-IDF Title & Abstract similarity, colored by dominant research topic. Hover over any point to inspect document metadata.

Filter & Search Parsed BibTeX Records

Showing 0 documents
🗂️ Complete Parsed Mendeley BibTeX Literature Table
100%
# Year Type Title & Abstract Excerpt Authors Journal / Venue Assigned Topic Mendeley Tags
Full metadata table extracted from the active .bib file. Export filtered or complete rows as formatted plain-text (.txt) or spreadsheet (.csv).

Mendeley Analytics Dashboard Repository

The dashboard source code (index.html) and the Mendeley .bib database files analyzed here are publicly available on GitHub. The dashboard automatically loads the newest .bib file found in the repository folder.

🔗 https://github.com/MohamedAbuella/Mendeley_Analytics_Dashboard (source code & data)
🌐 https://mohamedabuella.github.io/Mendeley_Analytics_Dashboard/ (live dashboard)