Mapping the intellectual structure of the Internet of Things (IoT) field based on web content: a co-word analysis
سال انتشار: 1399
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 827
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شناسه ملی سند علمی:
ISCELEC04_003
تاریخ نمایه سازی: 27 مرداد 1399
چکیده مقاله:
Despite twenty years from the Internet of Things advent, there has been a serious weakness in theintellectual structure of this field. Most papers in the intellectual structure were conducted on databasessuch as Web of Science while a large amount of information has lied on web pages. Furthermore, due tothe time-consuming process for scientific articles to get published, the information existing in onlinedatabases is not as up-to-date as those available on blogs and web pages. Therefore, in this paper, theintellectual structure of the Internet of Things weblogs is studied by the use of web mining methods,mainly the co-word analysis. Data was gathered by crawling the top 100 blogs of the Internet of Things,which altogether 3200 links including 92966 paragraphs were extracted. A list of the most frequently usedkeywords and key phrases were prepared for analyzing by co-word analysis. The co-word network of theInternet of Things is then visualized. The findings reveal eight communities, including Communications,Security, Artificial Intelligence, Infrastructure, Transportation, Intelligence, and Social Network. One ofthe exciting outputs of this study is the way each famous company behaves with regard to IoT. Besides,effective areas of the Internet of Things were determined that finally infrastructures of the Internet ofThings were identified as the most effective field.
کلیدواژه ها:
Internet of Things (IoT) ، Co-word Analysis ، Effective Areas ، Web Content Mining ، Intellectual Structure ، Community Detection
نویسندگان
Hamed Baziyad
M.Sc., Department of Information Technology, Faculty of Industrial and Systems Engineering, Tarbiat Modare University, Tehran, Iran
Rasoul Norouzi
M.Sc., Department of Information Technology, Faculty of Industrial and Systems Engineering, Tarbiat Modare University, Tehran, Iran
Elham Akhondzadeh
Associate Professor, Department of Information Technology, Faculty of Industrial and Systems Engineering, Tarbia Modares University, Tehran, Iran
Amir Albadvi
Professor, Department of Information Technology, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran