个人信息Personal Information
教授
博士生导师
硕士生导师
任职 : 中国工程科技创新战略研究院客座教授
性别:女
毕业院校:大连理工大学
学位:博士
所在单位:公共管理学院
学科:科学学与科技管理. 区域经济学
办公地点:大连理工大学人文楼301房间
联系方式:0411-84706082
电子邮箱:chenyue@dlut.edu.cn
Data Mining From Web Search Queries: A Comparison of Google Trends and Baidu Index
点击次数:
论文类型:期刊论文
发表时间:2015-01-01
发表刊物:JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY
收录刊物:SCIE、EI、SSCI、Scopus
卷号:66
期号:1
页面范围:13-22
ISSN号:2330-1635
关键字:web mining; webometrics
摘要:Numerous studies have explored the possibility of uncovering information from web search queries but few have examined the factors that affect web query data sources. We conducted a study that investigated this issue by comparing Google Trends and Baidu Index. Data from these two services are based on queries entered by users into Google and Baidu, two of the largest search engines in the world. We first compared the features and functions of the two services based on documents and extensive testing. We then carried out an empirical study that collected query volume data from the two sources. We found that data from both sources could be used to predict the quality of Chinese universities and companies. Despite the differences between the two services in terms of technology, such as differing methods of language processing, the search volume data from the two were highly correlated and combining the two data sources did not improve the predictive power of the data. However, there was a major difference between the two in terms of data availability. Baidu Index was able to provide more search volume data than Google Trends did. Our analysis showed that the disadvantage of Google Trends in this regard was due to Google's smaller user base in China. The implication of this finding goes beyond China. Google's user bases in many countries are smaller than that in China, so the search volume data related to those countries could result in the same issue as that related to China.