IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i7p2388-d339648.html
   My bibliography  Save this article

The Relationship Exploration between Public Migration Attention and Population Migration from a Perspective of Search Query

Author

Listed:
  • Chun Li

    (Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650091, Yunnan, China)

  • Jianhua He

    (School of Resources and Environment Science, Wuhan University, Wuhan 430079, Hubei, China)

  • Xingwu Duan

    (Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650091, Yunnan, China)

Abstract

Rapid population migration has been viewed as a critical factor impacting urban network construction and regional sustainable development. The supervision and analysis of population migration are necessary for guiding the optimal allocation of urban resources and for attaining the high efficiency development of region. Currently, the explorations of population migration are often restricted by the limitation of data. In the information era, search engines widely collect public attention, implying potential individual actions, and freely provide open, timelier, and large-scope search query data for helping explore regional phenomena and problems. In this paper, we endeavor to explore the possibility of adopting such data to depict population migration. Based on the search query from Baidu search engine, three migration attention indexes (MAIs) are constructed to capture public migration attention in cyber space. Taking three major urban agglomerations in China as case study, we conduct the correlation analysis among the cyber MAIs and population migration in geographical space. Results have shown that external-MAI and local-MAI can positively reflect the population migration inner regions and across regions from a holistic lens and that intercity-MAI can be a helpful supplement for the delineation of specific population flow. Along with the accumulation of cyber search query data, its potential in exploring population migration can be further reinforced.

Suggested Citation

  • Chun Li & Jianhua He & Xingwu Duan, 2020. "The Relationship Exploration between Public Migration Attention and Population Migration from a Perspective of Search Query," IJERPH, MDPI, vol. 17(7), pages 1-18, April.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:7:p:2388-:d:339648
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/7/2388/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/7/2388/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tianxiang Li & Beibei Wu & Fujin Yi & Bin Wang & Tomas Baležentis, 2020. "What Happens to the Health of Elderly Parents When Adult Child Migration Splits Households? Evidence from Rural China," IJERPH, MDPI, vol. 17(5), pages 1-14, March.
    2. Zhao, Yaohui, 1999. "Labor Migration and Earnings Differences: The Case of Rural China," Economic Development and Cultural Change, University of Chicago Press, vol. 47(4), pages 767-782, July.
    3. Zhang, Kevin Honglin & Song, Shunfeng, 2003. "Rural-urban migration and urbanization in China: Evidence from time-series and cross-section analyses," China Economic Review, Elsevier, vol. 14(4), pages 386-400.
    4. Nikolaos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(2), pages 107-120.
    5. Kathleen Beegle & Joachim De Weerdt & Stefan Dercon, 2011. "Migration and Economic Mobility in Tanzania: Evidence from a Tracking Survey," The Review of Economics and Statistics, MIT Press, vol. 93(3), pages 1010-1033, August.
    6. Bosetti, Valentina & Cattaneo, Cristina & Verdolini, Elena, 2015. "Migration of skilled workers and innovation: A European Perspective," Journal of International Economics, Elsevier, vol. 96(2), pages 311-322.
    7. Appleton, Simon & Song, Lina, 2008. "Life Satisfaction in Urban China: Components and Determinants," World Development, Elsevier, vol. 36(11), pages 2325-2340, November.
    8. Konstantin Kholodilin & Maximilian Podstawski & Boriss Siliverstovs, 2010. "Do Google Searches Help in Nowcasting Private Consumption?," KOF Working papers 10-256, KOF Swiss Economic Institute, ETH Zurich.
    9. 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.
    10. Xu Tian & Caicui Ding & Chong Shen & Hui Wang, 2017. "Does Parental Migration Have Negative Impact on the Growth of Left-Behind Children?—New Evidence from Longitudinal Data in Rural China," IJERPH, MDPI, vol. 14(11), pages 1-10, October.
    11. Xiushi Yang, 2000. "Determinants of Migration Intentions in Hubei Province, China: Individual versus Family Migration," Environment and Planning A, , vol. 32(5), pages 769-787, May.
    12. Konstantin A. Kholodilin & Maximilian Podstawski & Boriss Siliverstovs, 2010. "Do Google Searches Help in Nowcasting Private Consumption?: A Real-Time Evidence for the US," Discussion Papers of DIW Berlin 997, DIW Berlin, German Institute for Economic Research.
    13. Ren, Yu & Xiong, Cong & Yuan, Yufei, 2012. "House price bubbles in China," China Economic Review, Elsevier, vol. 23(4), pages 786-800.
    14. Jingjing Lu & Minmin Jiang & Lu Li & Therese Hesketh, 2019. "Relaxation in the Chinese Hukou System: Effects on Psychosocial Wellbeing of Children Affected by Migration," IJERPH, MDPI, vol. 16(19), pages 1-9, October.
    15. Changyu Fan & Linping Liu & Wei Guo & Anuo Yang & Chenchen Ye & Maitixirepu Jilili & Meina Ren & Peng Xu & Hexing Long & Yufan Wang, 2020. "Prediction of Epidemic Spread of the 2019 Novel Coronavirus Driven by Spring Festival Transportation in China: A Population-Based Study," IJERPH, MDPI, vol. 17(5), pages 1-27, March.
    16. Yu Liu & Zhengwei Sui & Chaogui Kang & Yong Gao, 2014. "Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-11, January.
    17. Denise Hare, 1999. "'Push' versus 'pull' factors in migration outflows and returns: Determinants of migration status and spell duration among China's rural population," Journal of Development Studies, Taylor & Francis Journals, vol. 35(3), pages 45-72.
    18. Cuihong Long & Jiajun Han & Yong Liu, 2020. "Has Rural-Urban Migration Promoted the Health of Chinese Migrant Workers?," IJERPH, MDPI, vol. 17(4), pages 1-22, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fei Ma & Yujie Zhu & Kum Fai Yuen & Qipeng Sun & Haonan He & Xiaobo Xu & Zhen Shang & Yan Xu, 2022. "Exploring the Spatiotemporal Evolution and Sustainable Driving Factors of Information Flow Network: A Public Search Attention Perspective," IJERPH, MDPI, vol. 19(1), pages 1-25, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Chien-jung Ting & Yi-Long Hsiao, 2022. "Nowcasting the GDP in Taiwan and the Real-Time Tourism Data," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 12(3), pages 1-2.
    3. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
    4. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
    5. Chien-jung Ting & Yi-Long Hsiao & Rui-jun Su, 2022. "Application of the Real-Time Tourism Data in Nowcasting the Service Consumption in Taiwan," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(4), pages 1-4.
    6. Aimin Chen & N. Edward Coulson, 2002. "Determinants of Urban Migration: Evidence from Chinese Cities," Urban Studies, Urban Studies Journal Limited, vol. 39(12), pages 2189-2197, November.
    7. Kholodilin, Konstantin A. & Siliverstovs, Boriss, 2012. "Measuring regional inequality by internet car price advertisements: Evidence for Germany," Economics Letters, Elsevier, vol. 116(3), pages 414-417.
    8. Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
    9. Siliverstovs, Boriss & Wochner, Daniel S., 2018. "Google Trends and reality: Do the proportions match?," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 1-23.
    10. David Iselin & Boriss Siliverstovs, 2013. "Using Newspapers for Tracking the Business Cycle," KOF Working papers 13-337, KOF Swiss Economic Institute, ETH Zurich.
    11. Chun Li & Xingwu Duan, 2020. "Exploration of Urban Interaction Features Based on the Cyber Information Flow of Migrant Concern: A Case Study of China’s Main Urban Agglomerations," IJERPH, MDPI, vol. 17(12), pages 1-20, June.
    12. Vicente, María Rosalía & López-Menéndez, Ana J. & Pérez, Rigoberto, 2015. "Forecasting unemployment with internet search data: Does it help to improve predictions when job destruction is skyrocketing?," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 132-139.
    13. Georgios Bampinas & Theodore Panagiotidis & Christina Rouska, 2019. "Volatility persistence and asymmetry under the microscope: the role of information demand for gold and oil," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 180-197, February.
    14. David Iselin & Boriss Siliverstovs, 2013. "Mit Zeitungen Konjunkturprognosen erstellen: Eine Vergleichsstudie für die Schweiz und Deutschland," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, vol. 7(3), pages 104-117, September.
    15. Gomes, Pedro & Taamouti, Abderrahim, 2016. "In search of the determinants of European asset market comovements," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 103-117.
    16. Xia Sun & Juan Chen & Shenghua Xie, 2022. "Becoming Urban Citizens: A Three-Phase Perspective on the Social Integration of Rural–Urban Migrants in China," IJERPH, MDPI, vol. 19(10), pages 1-19, May.
    17. Tong Liu & Guojun He & Alexis Lau, 2018. "Avoidance behavior against air pollution: evidence from online search indices for anti-PM2.5 masks and air filters in Chinese cities," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 20(2), pages 325-363, April.
    18. Karaman Örsal, Deniz Dilan, 2021. "Onlinedaten und Konsumentscheidungen: Voraussagen anhand von Daten aus Social Media und Suchmaschinen," Edition HWWI: Chapters, in: Straubhaar, Thomas (ed.), Neuvermessung der Datenökonomie, volume 6, pages 157-172, Hamburg Institute of International Economics (HWWI).
    19. Smith, Geoffrey Peter, 2012. "Google Internet search activity and volatility prediction in the market for foreign currency," Finance Research Letters, Elsevier, vol. 9(2), pages 103-110.
    20. Ying Liu & Rongrong Zhang & Ming Li & Chunshan Zhou, 2020. "What Factors Influence Rural-To-Urban Migrant Peasants to Rent out Their Household Farmland? Evidence from China’s Pearl River Delta," Land, MDPI, vol. 9(11), pages 1-19, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:7:p:2388-:d:339648. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.