📊 Bibliometric Regression Analysis of Library Marketing Impact (2010–2025)

This project performs a bibliometric linear regression analysis to explore the relationship between the number of indexed research documents and the total citation impact of authors publishing in the field of library marketing.

The analysis relies on bibliometric data extracted from Web of Science (WoS) and processed through InCites (Clarivate Analytics).

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📥 Data Source

The dataset was retrieved from the Web of Science Core Collection and enriched with metrics using InCites (Clarivate Analytics). The exported CSV file includes the following variables:

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🔍 Boolean Search Strategy

Boolean query used to retrieve data:

("library marketing" OR "marketing in libraries" OR "library promotion") AND (impact OR evaluation OR effectiveness OR engagement) NOT (editorial OR "book review" OR commentary)

Web of Science TS field equivalent:

(((TS = "library marketing") OR (TS = "marketing in libraries")) OR (TS = "library promotion")) AND((((TS = impact) OR (TS = evaluation)) OR (TS = effectiveness)) OR (TS = engagement)) NOT((((TS = editorial) OR (TS = "book review")) OR (TS = commentary)))

How to Run the Project

# 1. Create virtual environment
python -m venv .venv
.\.venv\Scripts\activate   # On Windows

# 2. Install dependencies
pip install -r requirements.txt

# 3. Clean raw dataset
python src/clean_data.py

# 4. Run regression analysis
python src/run_regression.py

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