Ten years of research change using Google Trends: From the perspective of big data utilizations and applications

被引:287
作者
Jun, Seung-Pyo [1 ,2 ]
Yoo, Hyoung Sun [1 ,2 ]
Choi, San [1 ,2 ]
机构
[1] Korea Inst Sci & Technol Informat, Technol Commercializat Anal Ctr, 66 Hoegi Ro, Seoul 130741, South Korea
[2] Univ Sci & Technol, Sci & Technol Management & Policy, 66 Hoegi Ro, Seoul 130741, South Korea
关键词
Google Trends; Big data utilization; Big data application; Networks analysis; Author keyword; Science Journal Classification; Clustering; PRIOR KNOWLEDGE; IMPACT FACTOR; SEARCH DATA; EXPECTATIONS; INFORMATION; CENTRALITY; INTERNET;
D O I
10.1016/j.techfore.2017.11.009
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study seeks to analyze the trends in research studies in the past decade which have utilized Google Trends, a new source of big data, to examine how the scope of research has expanded. Our purpose is to conduct a comprehensive and objective research into how the public use of Big Data from web searches has affected research, and furthermore, to discuss the implications of Google Trends in terms of Big Data utilization and application. To this end, we conducted a network analysis on 657 research papers that used Google Trends. We also identified the important nodes of the networks and reviewed the research directions of representative papers. The study reveals that Google Trends is used to analyze various variables in a wide range of areas, including IT, communications, medicine, health, business and economics. In addition, this study shows that research using Google Trends has increased dramatically in the last decade, and in the process, the focus of research has shifted to forecasting changes, whereas in the past the focus had been on merely describing and diagnosing research trends, such as surveillance and monitoring. This study also demonstrates that in recent years, there has been an expansion in analysis in linkage with other social Big Data sources, as researchers attempt to overcome the limitations of using only search information. Our study will provide various insights for researchers who utilize Google Trends as well as researchers who rely on various other sources of Big Data in their efforts to compare research trends and identify new areas for research.
引用
收藏
页码:69 / 87
页数:19
相关论文
共 88 条
[1]   Patterns of expectations for emerging sustainable technologies [J].
Alkemade, Floortje ;
Suurs, Roald A. A. .
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2012, 79 (03) :448-456
[2]   Prediction of Dengue Incidence Using Search Query Surveillance [J].
Althouse, Benjamin M. ;
Ng, Yih Yng ;
Cummings, Derek A. T. .
PLOS NEGLECTED TROPICAL DISEASES, 2011, 5 (08)
[3]   Differences in Impact Factor Across Fields and Over Time [J].
Althouse, Benjamin M. ;
West, Jevin D. ;
Bergstrom, Carl T. ;
Bergstrom, Theodore .
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, 2009, 60 (01) :27-34
[4]  
[Anonymous], INT J SMART HOME
[5]  
[Anonymous], 2012, Social Network Analysis
[6]  
[Anonymous], 1993, The Stanford graph base: A platform for combinatorial computing
[7]  
Askitas, 2009, APPL EC Q, V55, P107, DOI [DOI 10.3790/AEQ.55.2.107, 10.2139/ssrn.1465341, 10.3790/aeq.55.2.107]
[8]  
Assael H., 1992, CONSUMER BEHAV MARKE
[9]  
Bastian M., 2009, 3 INT AAAI C WEBLOGS, DOI [10.13140/2.1.1341.1520, DOI 10.1609/ICWSM.V3I1.13937]
[10]   EXTERNAL SEARCH EFFORT - AN INVESTIGATION ACROSS SEVERAL PRODUCT CATEGORIES [J].
BEATTY, SE ;
SMITH, SM .
JOURNAL OF CONSUMER RESEARCH, 1987, 14 (01) :83-95