From Text to Understanding
Using Fuzzy Sets to Analyse Free-Form Text Data
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Beschreibung
Social media and other sources of text data are still underutilized resources in public decision-making. Most public organizations and governmental bodies rely mainly only surveys, interviews and other traditional methods for gathering opinions. One issues is a lack of easy-to-use tools for mass text data processing that would enable these organizations to process and understand this type of data.
This book introduces a novel text data analysis framework designed for public decision making, specifically on the level of municipalities. The framework combines sentiment analysis with topic modelling and a fuzzy-based approach for capturing the diversity in sentiment arising from the fact that different people have different opinions on a given topic.
The book is recommended for practitioners in public decision making as well as researchers analyzing large amounts of text data in order to understand people’s opinions.
Social media and other sources of text data are still underutilized resources in public decision-making. Most public organizations and governmental bodies rely mainly only surveys, interviews and other traditional methods for gathering opinions. One issues is a lack of easy-to-use tools for mass text data processing that would enable these organizations to process and understand this type of data.
This book introduces a novel text data analysis framework designed for public decision making, specifically on the level of municipalities. The framework combines sentiment analysis with topic modelling and a fuzzy-based approach for capturing the diversity in sentiment arising from the fact that different people have different opinions on a given topic.
The book is recommended for practitioners in public decision making as well as researchers analyzing large amounts of text data in order to understand people’s opinions.
Presents a unique combination of fuzzy approaches and NLP methods Demonstrates how to capture the diversity of opinions and make effective use of the information obtained Illustrates how fuzzy and NLP methods can be used to support public decision making
Autor*in
Miloš Švaňa
Themen in »From Text to Understanding«
Natural Language Processing NLP Fuzzy sets Smart cities Text data analysis Sentiment analysis Social media public decision making Topic modelling