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Who is the most sought‐after economist? Ranking economists using Google Trends

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  • Tom Coupé

Abstract

This paper uses Google Trends to rank economists and discusses the advantages and disadvantages of using Google Trends compared with other ranking methods, like those based on citations or downloads. I find that Google search intensity rankings make it possible to compare the current impact of both contemporaneous and past economists and that they can help to illustrate the variety in economists' careers that can lead to fame. Given Google Trends' algorithm to allocate searches to individuals (Google Trends' “topics”) is only applied to individuals with sufficiently high search intensity, Google Trends can only be used to rank about 2000 economists who have been regularly searched for on Google. For these sought‐after economists, I find that search intensity rankings based on Google Trends data are only modestly correlated with more traditional measures of scholarly impact.

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  • Tom Coupé, 2022. "Who is the most sought‐after economist? Ranking economists using Google Trends," Southern Economic Journal, John Wiley & Sons, vol. 89(2), pages 611-642, October.
  • Handle: RePEc:wly:soecon:v:89:y:2022:i:2:p:611-642
    DOI: 10.1002/soej.12606
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    1. 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.
    2. Melody Lo & M.C. Sunny Wong & Franklin G. Mixon Jr, 2008. "Ranking Economics Journals, Economics Departments, and Economists Using Teaching-Focused Research Productivity," Southern Economic Journal, John Wiley & Sons, vol. 74(3), pages 894-906, January.
    3. Philippe Mongeon & Adèle Paul-Hus, 2016. "The journal coverage of Web of Science and Scopus: a comparative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 213-228, January.
    4. William L. Davis & Bob G. Figgins & David Hedengren & Daniel B. Klein, 2011. "Economics Professors' Favorite Economic Thinkers, Journals, and Blogs (along with Party and Policy Views)," Econ Journal Watch, Econ Journal Watch, vol. 8(2), pages 126-146, May.
    5. Mike Thelwall, 2021. "Measuring Societal Impacts Of Research With Altmetrics? Common Problems And Mistakes," Journal of Economic Surveys, Wiley Blackwell, vol. 35(5), pages 1302-1314, December.
    6. Aloys Prinz, 2017. "Memorability of Nobel Prize laureates in economics," Applied Economics Letters, Taylor & Francis Journals, vol. 24(6), pages 433-437, March.
    7. Martín-Martín, Alberto & Orduna-Malea, Enrique & Thelwall, Mike & Delgado López-Cózar, Emilio, 2018. "Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories," Journal of Informetrics, Elsevier, vol. 12(4), pages 1160-1177.
    8. Tom Coupé, 2003. "Revealed Performances: Worldwide Rankings of Economists and Economics Departments, 1990-2000," Journal of the European Economic Association, MIT Press, vol. 1(6), pages 1309-1345, December.
    9. Philip Hans Franses, 2014. "Trends in three decades of rankings of Dutch economists," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 1257-1268, February.
    10. Seiler, Christian & Wohlrabe, Klaus, 2012. "Ranking economists on the basis of many indicators: An alternative approach using RePEc data," Journal of Informetrics, Elsevier, vol. 6(3), pages 389-402.
    11. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    12. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
    13. Sturm Jan-Egbert & Ursprung Heinrich W., 2017. "The Handelsblatt Rankings 2.0: Research Rankings for the Economics Profession in Austria, Germany, and Switzerland," German Economic Review, De Gruyter, vol. 18(4), pages 492-515, December.
    14. John H. Huston & Roger W. Spencer, 2018. "Using Network Centrality to Inform Our View of Nobel Economists," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 44(4), pages 616-628, September.
    15. Liwen Vaughan & Esteban Romero-Frías, 2014. "Web search volume as a predictor of academic fame: An exploration of Google trends," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 707-720, April.
    16. Mohammad Reza Farzanegan & Mehdi Feizi & Saeed Malek Sadati, 2020. "Google It Up! A Google Trends-based analysis of COVID-19 outbreak in Iran," MAGKS Papers on Economics 202017, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
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    JEL classification:

    • A11 - General Economics and Teaching - - General Economics - - - Role of Economics; Role of Economists
    • B30 - Schools of Economic Thought and Methodology - - History of Economic Thought: Individuals - - - General

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