| Autor: |
Xiangjie Kong, Kai Ma, Shen Hou, Di Shang, Feng Xia |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 7, Pp 4611-4628 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2018.2887341 |
| Popis: |
As a common human behavior, interaction is everywhere in human life. With the rise of big data and human–computer interaction in the 21st century, more and more researchers from different industries and disciplines pay great attention to the human interactive behavior research. From the perspective of computer science, scholars try to use computer technology to make research more meaningful. To the best of our knowledge, this paper is the first study to investigate the potential rules of human interactive behavior in the view of computer science, based on 16 top-tier journals of human interactive behavior from Microsoft Academic Graph dataset. We put forward a topic extraction and clustering model based on word2vec to infer key topics, which can be widely used in different fields of research. We find that the growth of human interactive behavior is in an uptrend on the whole. Besides, the cooperative relationship between authors and countries/regions is closer over time. We also make the mensurable evolution analysis of topics by a statistical method. Some topics are hot all the time, while some are unpopular as time goes by. Finally, we do rankings in the field of human behavior research from a new perspective. All these findings help researchers observe potential patterns and the topic evolution in half a century, which may shed dazzling light on the exploration of human interactive behavior. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
