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Data mining from web search queries: A comparison of google trends and baidu index

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  • Liwen Vaughan
  • Yue Chen

Abstract

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Suggested Citation

  • Liwen Vaughan & Yue Chen, 2015. "Data mining from web search queries: A comparison of google trends and baidu index," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(1), pages 13-22, January.
  • Handle: RePEc:bla:jinfst:v:66:y:2015:i:1:p:13-22
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    File URL: http://hdl.handle.net/10.1002/asi.23201
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    Cited by:

    1. Martin Obschonka & Mingjie Zhou & Yixin Zhou & Jianxin Zhang & Rainer K. Silbereisen, 2019. "“Confucian” traits, entrepreneurial personality, and entrepreneurship in China: a regional analysis," Small Business Economics, Springer, vol. 53(4), pages 961-979, December.
    2. Houcemeddine Turki & Mohamed Ali Hadj Taieb & Mohamed Ben Aouicha & Ajith Abraham, 2020. "Nature or Science: what Google Trends says," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1367-1385, August.
    3. Yu Qin & Hongjia Zhu, 2018. "Run away? Air pollution and emigration interests in China," Journal of Population Economics, Springer;European Society for Population Economics, vol. 31(1), pages 235-266, January.
    4. Houcemeddine Turki & Mohamed Ali Hadj Taieb & Mohamed Ben Aouicha & Ajith Abraham, 0. "Nature or Science: what Google Trends says," Scientometrics, Springer;Akadémiai Kiadó, vol. 0, pages 1-19.
    5. Jianchun Fang & Wanshan Wu & Zhou Lu & Eunho Cho, 2019. "Using Baidu Index To Nowcast Mobile Phone Sales In China," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(01), pages 83-96, March.
    6. Fan, Xiaoqian & Yuan, Ying & Zhuang, Xintian & Jin, Xiu, 2017. "Long memory of abnormal investor attention and the cross-correlations between abnormal investor attention and trading volume, volatility respectively," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 323-333.
    7. Schaer, Oliver & Kourentzes, Nikolaos & Fildes, Robert, 2019. "Demand forecasting with user-generated online information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 197-212.
    8. Stephen L. France & Yuying Shi, 2017. "Aggregating Google Trends: Multivariate Testing and Analysis," Papers 1712.03152, arXiv.org, revised Mar 2018.
    9. Jun, Seung-Pyo & Yoo, Hyoung Sun & Choi, San, 2018. "Ten years of research change using Google Trends: From the perspective of big data utilizations and applications," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 69-87.

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