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research-trend-analysis

Analyze research trends in academic publications using Python.

2|1|Updated May 11, 2026
Search Tags:#network visualization#trend analysis#keyword analysis#academic analysis#research trends
One-click install
npx skills add https://github.com/LittleSongxx/SoulSearcher --skill research-trend-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: research-trend-analysis
Source: https://github.com/LittleSongxx/SoulSearcher/tree/main/skills/public/research-trend-analysis
Command: npx skills add https://github.com/LittleSongxx/SoulSearcher --skill research-trend-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, matplotlib, networkx, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a comprehensive analysis of research trends, enabling users to quickly understand the evolution of research areas over time.

Core Features & Use Cases

  • Quantitative Analysis: Analyze research trends across academic publications with detailed metrics.
  • Sub-Topic Mining: Identify emerging and declining research areas through keyword and topic analysis.
  • Network Analysis: Visualize keyword co-occurrence networks and analyze author and institution contributions.
  • Visualization and Reporting: Generate trend charts and structured reports for easy interpretation.
  • Use Case: When deciding on a research direction or writing a survey, use this Skill to assess the momentum of different research areas.

Quick Start

Analyze the research trends in the field of "machine learning" using the research-trend-analysis skill.

Frequently Asked Questions about research-trend-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze research trends in academic publications to identify emerging topics?▼

You can visualize keyword co-occurrence networks by running Python-based trend calculations on academic publication data. This Skill generates network visualizations using matplotlib and networkx to map relationships between keywords, authors, and institutions.

Do I need Python to perform keyword analysis and generate trend charts?▼

Yes, you need Python to perform keyword analysis and generate trend charts. The Skill relies on a Python environment utilizing pandas and numpy for quantitative data analysis, and matplotlib for rendering the visual trend reports.

What is the best way to assess the momentum of different research areas for a survey?▼

This Skill supports trend analysis for large volumes of academic publications by leveraging pandas and numpy for data processing. It handles extensive datasets to calculate metrics, identify emerging topics, and generate comprehensive network visualizations.

When should I not use automated academic analysis for research direction decisions?▼

You should not rely solely on automated academic analysis when publications lack structured metadata or when researching entirely novel fields with minimal database presence. The effectiveness of trend calculations and keyword analysis depends on the availability of historical publication data.

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