Bibliometric and Network Analysis of Scientific Studies on Family Business Succession
✅ Data Collection:
• Retrieve academic publications from Scopus, Web of Science, and Google Scholar using key terms related to family business succession.
• Ensure that data includes title, authors, journal/conference, publication year, citations, DOI (if available), and references (citation links).
• The dataset should cover recent years (2022-2024) to ensure relevance.
✅ Data Processing & Analysis:
• Clean and preprocess bibliometric data (removing duplicates, normalizing author names, handling missing values).
• Conduct co-authorship network analysis (identifying collaborations between researchers).
• Perform citation network analysis (who cites whom).
• Run keyword co-occurrence analysis (to detect research trends and topics).
• Calculate standard network metrics: centrality (degree, betweenness, closeness), density, modularity, etc.
✅ Visualization & Reporting:
• Create network graphs using Gephi, VOSviewer, or Python (NetworkX, Matplotlib, Plotly).
• Provide clear visualizations of co-authorship, citation networks, and keyword clustering.
• Summarize key findings in a structured report, including leading researchers, key research directions, and emerging trends.
Requirements:
🔹 Experience with bibliometric analysis & network science
🔹 Proficiency in tools like VOSviewer, Gephi, or Python (NetworkX, Pandas)
🔹 Ability to work with Scopus/Web of Science data and academic databases
🔹 Experience in data visualization & academic writing is a plus