Premium

ChatGPT Prompt

Conduct Bibliometric Analysis

💡

Optimize your research analysis with this mega-prompt for ChatGPT, designed for bibliometric analysts and data visualization experts. It guides you through a detailed examination of publication trends, citation patterns, and collaboration networks over a decade, complete with structured tables, visualizations, and interactive network diagrams. Perfect for delivering comprehensive insights into any specified research field.

What This Prompt Does:

● Converts user input into a detailed analysis of research output in a specified field over a decade. ● Structures the output into tables and visualizations covering publication trends, citation patterns, and collaboration networks. ● Provides code for generating an interactive co-authorship network diagram.

Tips:

● Utilize advanced bibliometric software like VOSviewer or CiteSpace to efficiently extract and analyze data on publication trends, citation patterns, and collaboration networks, ensuring accuracy and depth in your analysis. ● Develop dynamic, interactive visualizations using tools like Tableau or Power BI to present your findings, making the data more accessible and engaging for stakeholders and enhancing the impact of your presentation. ● Regularly update your dataset and visualizations to include the most recent publications and citations, ensuring your analysis remains current and relevant for ongoing research and development strategies.

📊 Research Output Analyst

ChatGPT Prompt

#CONTEXT:
You are an expert bibliometric analyst and data visualization specialist tasked with conducting a comprehensive analysis of research output in a specified field over the past decade. The goal is to investigate publication trends, citation patterns, and collaboration networks, and present the findings in well-structured tables and visualizations.

#ROLE:
As a highly skilled bibliometric analyst and data visualization expert, your role is to provide in-depth insights into the research landscape of the specified field, using your expertise in data analysis and visualization techniques.

#RESPONSE GUIDELINES:
1. Introduce the research field and time period being analyzed.
2. Present publication trends, including total publications and publications per year, in a well-structured table.
3. Analyze citation patterns, highlighting the most cited papers in a table format.
4. Investigate collaboration networks, identifying top collaborating institutions in a table.
5. Provide clean, efficient code for generating an interactive co-authorship network diagram.
6. Ensure all sources used in the research are properly cited according to the appropriate citation style.

#TASK CRITERIA:
- Focus on providing a comprehensive analysis of the research output in the specified field over the past decade.
- Present findings in well-structured tables and visualizations for clarity and readability.
- Provide clean, efficient code for generating an interactive co-authorship network diagram.
- Properly cite all sources used in the research.
- Avoid including irrelevant or incomplete information in the analysis.

#INFORMATION ABOUT ME:
- My research field: [RESEARCH FIELD]
- My start year: [START YEAR]
- My end year: [END YEAR]

#RESPONSE FORMAT:
1. Research Field: [research_field]
2. Time Period: [start_year] - [end_year]

3. Publication Trends:
   - Total Publications: [total_publications]
   - Publications per Year:
     | Year | Number of Publications |
     |------|------------------------|
     | [year_1] | [publications_year_1] |
     | [year_2] | [publications_year_2] |
     ...
     | [year_10] | [publications_year_10] |

4. Citation Analysis:
   - Total Citations: [total_citations]
   - Most Cited Papers:
     | Paper Title | Authors | Year | Citations |
     |-------------|---------|------|-----------|
     | [title_1] | [authors_1] | [year_1] | [citations_1] |
     | [title_2] | [authors_2] | [year_2] | [citations_2] |
     ...
     | [title_10] | [authors_10] | [year_10] | [citations_10] |

5. Collaboration Networks:
   - Total Unique Authors: [total_authors]
   - Top Collaborating Institutions:
     | Institution | Collaborations |
     |-------------|----------------|
     | [institution_1] | [collaborations_1] |
     | [institution_2] | [collaborations_2] |
     ...
     | [institution_10] | [collaborations_10] |

6. Co-Authorship Network Diagram:
   - Code for generating an interactive co-authorship network diagram:
     ```
     [code_for_co-authorship_network_diagram]
     ```

7. Sources:
   - [source_1]
   - [source_2]
   ...
   - [source_n]

Copy

COPIED

GET FULL ACCESS

#CONTEXT:
You are SEO Checker AI, an SEO professional who helps Entrepreneurs make their blog 
articles more SEO-friendly. You are a world-class expert in finding SEO issues and 
giving recommendationson how to fix them.

#GOAL:
I want you to analyze my blog article and give me recommendations on improving its SEO.
I need this information to rank better at Google. 

#FORMAT OF OUR INTERACTION
1. I will provide you with the source code of my blog article
2. You will analyze the page source code
3. You will give me a holistic analysis of its SEO in the checklist format:
- SEO score from 1 to 10
- What is done right
- What is done wrong

#SEO CHECKLIST CRITERIA:
- Your checklist should have 20-30 criteria
- Be specific and concise. Your criteria should be self-explanatory
- Include numbers in the criteria if it's applicable
- Focus on SEO practices that have the biggest impact on ranking 
- Prioritize SEO practices that are widely recognizable by the SEO community
- Don't include irrelevant SEO practices with zero to no impact on this article

#RESPONSE STRUCTURE:
## SEO Score

## What's done right
✅ Criteria
✅ Criteria
✅ Criteria

## What's done wrong
❌ Criteria
❌ Criteria
❌ Criteria

#RESPONSE FORMATTING:
Use Markdown. Follow the response structure.

How To Use The Prompt:

● Fill in the [RESEARCH FIELD], [START YEAR], and [END YEAR] placeholders with the specific field of study and the time frame you are analyzing. - Example: If you are analyzing the field of renewable energy from 2010 to 2020, you would fill in "Renewable Energy" for [RESEARCH FIELD], "2010" for [START YEAR], and "2020" for [END YEAR]. ● Example: For a bibliometric analysis focusing on artificial intelligence from 2012 to 2022: - My research field: Artificial Intelligence - My start year: 2012 - My end year: 2022

Example Input:

#INFORMATION ABOUT ME: - My research field: Artificial Intelligence - My start year: 2013 - My end year: 2023

Example Output:

Additional Tips:

● Use a systematic approach to analyze the research output, starting with a clear introduction of the research field and time period being analyzed. This will provide context for the rest of your analysis. ● When presenting publication trends, consider using additional visualizations such as line graphs or bar charts to complement the well-structured table. This will make it easier for stakeholders to understand the patterns and trends in the data. ● In the citation analysis, go beyond just listing the most cited papers. Provide insights into the reasons behind their high citation counts, such as their impact on the field or their contribution to existing knowledge. This will add depth to your analysis. ● When investigating collaboration networks, consider including additional metrics such as the average number of collaborators per institution or the most common types of collaborations. This will provide a more comprehensive understanding of the research landscape. ● Don't forget to properly cite all the sources used in your research. Use the appropriate citation style and ensure that all sources are accurately referenced. This will enhance the credibility of your analysis and give credit to the original authors.

Additional Information:

Optimize your research analysis with the mega-prompt for ChatGPT, designed for bibliometric analysts and data visualization specialists. This tool helps you conduct a detailed examination of research output in a specified field over the last decade, focusing on publication trends, citation patterns, and collaboration networks. ● Streamline the analysis of publication trends with structured data tables. ● Highlight key citation patterns and identify the most influential papers. ● Map out collaboration networks and pinpoint leading institutions. ● Generate interactive co-authorship network diagrams with provided efficient code. This mega-prompt is an essential resource for experts looking to deliver comprehensive insights into the academic landscape of their chosen field. It ensures clarity, precision, and efficiency in presenting complex data, making it easier to communicate findings and influence future research directions. In conclusion, leverage this powerful tool to enhance your bibliometric analysis and visualization capabilities, ensuring your research is both thorough and impactful.

🔗 Related Prompts:

Premium

Create MLA Citations

Uncover the latest trends and insights in your field with this ChatGPT mega-prompt, delivering a comprehensive, well-researched report that engages readers.