کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
552449 | 873229 | 2008 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Analyzing unstructured text data: Using latent categorization to identify intellectual communities in information systems
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
سیستم های اطلاعاتی
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چکیده انگلیسی
The Information Systems field is structured by the research topics emphasized by communities of journals. The Latent Categorization Method categorized and automatically named IS research topics in 14,510 abstracts from 65 Information Systems journals. These topics were clustered into seven intellectual communities based on publication patterns. The technique develops categories from the data itself, it is replicable, is relatively insensitive to the size of the text units, and it avoids many of the problems that frequently accompany human categorization. As such LCM provides a new approach to analyzing a wide array of textual data.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Decision Support Systems - Volume 45, Issue 4, November 2008, Pages 884–896
Journal: Decision Support Systems - Volume 45, Issue 4, November 2008, Pages 884–896
نویسندگان
Kai R. Larsen, David E. Monarchi, Dirk S. Hovorka, Christopher N. Bailey,