Text Analysis at Penn Libraries

Computational Text Analysis, Computer-aided Text Analysis, Text Mining, and the abbreviation TDM are broad terms for searching, organizing, and analyzing large amounts of text data.

TDM can help reveal new patterns or information from a large body of work - leading to the development of new knowledge, of a larger evidence-based practice. TDM enables researchers to analyze thousands of documents and terabytes of data, allowing for a comprehensive look into research questions.

The methods used to process corpora vary widely between disciplines, and are based on insights from machine learning, statistics, computational linguistics, sociology, and many other fields. 

Examples where Researchers used text analysis to answer their research question

• Sentiment Analysis on Twitter Data mining
• Historical Newspaper Text Analysis with TDM Platforms
• Web Scraping open data from Museum websites Workshop Tutorial
• Extracting text from books and text visualization of term frequencies
• Authorship Attribution / Stylometric Analysis techniques

• Python
• R
• Data & GIS
• FAIR Data
• Data Management Resources
• Social Network Analysis
• Research Data Training Tutorials

Please check the Qualitative Data Analysis Libguide for Qualitative research tools and techniques, including NVivo, Atlas.ti, etc.