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Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

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Textual Analysis and Data Mining: An Interpreting Research on Nursing.

W De Caro¹, L Mitello¹, A R Marucci¹

¹Roma/IT, University of Rome sapienza.

Studies in Health Technology and Informatics

|June 23, 2016

Summary

Web data analysis reveals insights into nursing care. Text mining tools extract information on public perception, scientific activity, and visibility within healthcare discussions.

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Area of Science:

Digital Health
Health Informatics
Social Sciences

Background:

The digital age presents a massive volume of textual data, offering unprecedented opportunities for social and healthcare analysis.
Understanding societal phenomena, particularly in nursing and healthcare, can be enhanced through the statistical analysis of this information.

Purpose of the Study:

To outline a strategic approach for textual statistical analysis of web and journal data.
To extract valuable information concerning nursing care, sentiment, perception, scientific activities, and visibility.

Main Methods:

Utilizing web-based Text Mining applications (e.g., DTM, Wordle, Voyant Tools, Taltac 2.10, Treecloud).
Analyzing textual data from a major Italian newspaper ('Repubblica') and an Italian scientific nursing journal (2012-2014).

Main Results:

Demonstrated the potential of Text Mining tools for information extraction from large textual datasets.
Extracted data on sentiment, perception, scientific activities, and visibility related to nursing care.

Conclusions:

Textual statistical analysis offers a powerful method for understanding healthcare and nursing.
Web 2.0 tools facilitate the extraction of meaningful insights from diverse information sources.