GREGOR WIEDEMANN EVALUATES TEXT MINING APPLICATIONS FOR SOCIAL SCIENCE STUDIES WITH RESPECT TO CONCEPTUAL INTEGRATION OF CONSCIOUSLY SELECTED METHODS, SYSTEMATIC OPTIMIZATION OF ALGORITHMS AND WORKFLOWS, AND METHODOLOGICAL REFLECTIONS RELATING TO EMPIRICAL RESEARCH. IN AN EXEMPLARY STUDY, HE INTRODUCES WORKFLOWS TO ANALYZE A CORPUS OF AROUND 600,000 NEWSPAPER ARTICLES ON THE SUBJECT OF “DEMOCRATIC DEMARCATION” IN GERMANY. HE PROVIDES A VALUABLE RESOURCE FOR INNOVATIVE MEASURES TO SOCIAL SCIENTISTS AND COMPUTER SCIENTISTS IN THE FIELD OF APPLIED NATURAL LANGUAGE PROCESSING.&NBSP;

Rese�a del editor:

Gregor Wiedemann evaluates text mining applications for social science studies with respect to conceptual integration of consciously selected methods, systematic optimization of algorithms and workflows, and methodological reflections relating to empirical research. In an exemplary study, he introduces workflows to analyze a corpus of around 600,000 newspaper articles on the subject of “democratic demarcation” in Germany. He provides a valuable resource for innovative measures to social scientists and computer scientists in the field of applied natural language processing.

"Sobre este t�tulo" puede pertenecer a otra edici�n de este libro.

Descripci�n de la librer�a

Ver la p�gina web de la librer�a