Topic Modeling and Classification of Cyberspace Papers Using Text Mining
محل انتشار: مجله مطالعات فضای مجازی، دوره: 2، شماره: 1
سال انتشار: 1396
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 539
فایل این مقاله در 23 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
این مقاله در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JCSS-2-1_006
تاریخ نمایه سازی: 20 آبان 1397
چکیده مقاله:
The global cyberspace networks provide individuals with platforms to can interact,exchange ideas, share information, provide social support, conduct business, create artistic media, play games, engage in political discussions, and many more. The term cyberspace has become a conventional means to describe anything associated with the Internet and the diverse Internet culture. In fact, cyberspace is an umbrella term that covers all issues occurring through the interaction of information systems and humans over these networks. Deep evaluation of the scientific articles on the cyberspace domain provides concentrated knowledge and insights about major trends of the field. Text mining tools and techniques enable the practitioners and scholars to discover significant trends in a large set of internationally validated papers. This study utilizes text mining algorithms to extract, validate, and analyze 1860 scientific articles on the cyberspace domain and provides insight over the future scientific directions or cyberspace studies
کلیدواژه ها:
نویسندگان
Babak Sohrabi
Professor, Department of IT Management, Faculty of Management, University of Tehran (UT), Tehran, Iran
Iman Raeesi Vanani
Assistant Professor of Industrial Management, Allameh Tabataba’I University (ATU), Tehran, Iran
Mohsen Baranizade Shineh
Master of IT Management, Faculty of Management, University of Tehran (UT), Tehran, Iran-