Google Trends of political parties in Europe: a fractal exploration

Abraham-Frois, G. (1998). Non-linear dynamics and endogenous cycles (Vol. 463). Springer Science & Business Media. Abraham-FroisG. 1998 Non-linear dynamics and endogenous cycles 463 Springer Science & Business Media Search in Google Scholar

Beyer, J. (2012). Acting in Good time–Conceptual reflections on the Sequencing of Political reform Processes. Central European Journal of Public Policy, 6(02), 4–28. BeyerJ. 2012 Acting in Good time–Conceptual reflections on the Sequencing of Political reform Processes Central European Journal of Public Policy 6 02 4 28 Search in Google Scholar

Box, G. E., & Jenkins, G. M. (1970). Time series models for forecasting and control. San Francisco. BoxG. E. JenkinsG. M. 1970 Time series models for forecasting and control San Francisco Search in Google Scholar

Curran, T., & Singh, R. (2011). E-democracy as the future face of democracy: a case study of the 2011 Irish elections. European View, 10(1), 25–31. CurranT. SinghR. 2011 E-democracy as the future face of democracy: a case study of the 2011 Irish elections European View 10 1 25 31 Search in Google Scholar

Dijkstra, L., Poelman, H., & Rodríguez-Pose, A. (2020). The geography of EU discontent. Regional Studies, 54(6), 737–753. DijkstraL. PoelmanH. Rodríguez-PoseA. 2020 The geography of EU discontent Regional Studies 54 6 737 753 Search in Google Scholar

Dylko, I. B. (2013). On the role of technology in political communication research. Javnost-The Public, 20(1), 55–69. DylkoI. B. 2013 On the role of technology in political communication research Javnost-The Public 20 1 55 69 Search in Google Scholar

Doornik, J. A., & Ooms, M. (2003). Computational aspects of maximum likelihood estimation of autoregressive fractionally integrated moving average models. Computational Statistics & Data Analysis, 42(3), 333–348. DoornikJ. A. OomsM. 2003 Computational aspects of maximum likelihood estimation of autoregressive fractionally integrated moving average models Computational Statistics & Data Analysis 42 3 333 348 Search in Google Scholar

Eviews 9. (2022). Eviews 9 [Software]. Irvin, CA: Quantitative Micro Software, LLC. Eviews 9 2022 Eviews 9 [Software] Irvin, CA Quantitative Micro Software, LLC Search in Google Scholar

Flores-Muñoz, F., Báez-García, A. J., & Gutiérrez-Barroso, J. (2019). Fractional differencing in stock market price and online presence of global tourist corporations. Journal of Economics, Finance and Administrative Science, 24(48), 194–204. Flores-MuñozF. Báez-GarcíaA. J. Gutiérrez-BarrosoJ. 2019 Fractional differencing in stock market price and online presence of global tourist corporations Journal of Economics, Finance and Administrative Science 24 48 194 204 Search in Google Scholar

Geweke, J., & Porter-Hudak, S. (1983). The estimation and application of long memory time series models. Journal of Time Series Analysis, 4(4), 221–238. GewekeJ. Porter-HudakS. 1983 The estimation and application of long memory time series models Journal of Time Series Analysis 4 4 221 238 Search in Google Scholar

Gibson, R. K., & McAllister, I. (2011). Do online election campaigns win votes? The 2007 Australian “YouTube” election. Political Communication, 28(2), 227–244. GibsonR. K. McAllisterI. 2011 Do online election campaigns win votes? The 2007 Australian “YouTube” election Political Communication 28 2 227 244 Search in Google Scholar

Gong, R. (2011). Internet politics and state media control: Candidate weblogs in Malaysia. Sociological Perspectives, 54(3), 307–328. GongR. 2011 Internet politics and state media control: Candidate weblogs in Malaysia Sociological Perspectives 54 3 307 328 Search in Google Scholar

Google. (2022). Google Trends https://trends.google.com/ Google 2022 Google Trends https://trends.google.com/ Search in Google Scholar

Graves, T., Gramacy, R., Watkins, N., & Franzke, C. (2017). A brief history of long memory: Hurst, Mandelbrot and the road to ARFIMA, 1951–1980. Entropy, 19(9), 437. GravesT. GramacyR. WatkinsN. FranzkeC. 2017 A brief history of long memory: Hurst, Mandelbrot and the road to ARFIMA, 1951–1980 Entropy 19 9 437 Search in Google Scholar

Granger, C. W., & Joyeux, R. (1980) An introduction to long-memory time series models and fractional differencing. Journal of Time Series Analysis, 1(1), 15–29. GrangerC. W. JoyeuxR. 1980 An introduction to long-memory time series models and fractional differencing Journal of Time Series Analysis 1 1 15 29 Search in Google Scholar

Huberty, M. (2015). Can we vote with our tweet? On the perennial difficulty of election forecasting with social media. International Journal of Forecasting, 31(3), 992–1007. HubertyM. 2015 Can we vote with our tweet? On the perennial difficulty of election forecasting with social media International Journal of Forecasting 31 3 992 1007 Search in Google Scholar

Hutter, S., & Kriesi, H. (Eds.). (2019). European party politics in times of crisis. Cambridge University Press. HutterS. KriesiH. (Eds.). 2019 European party politics in times of crisis Cambridge University Press Search in Google Scholar

Hurst, H. E. (1951) Long-term storage capacity of reservoirs. Trans. Amer. Soc. Civil Eng., 116, 770–808. HurstH. E. 1951 Long-term storage capacity of reservoirs Trans. Amer. Soc. Civil Eng. 116 770 808 Search in Google Scholar

Jun, S. P., Yoo, H. S., & Choi, S. (2018). Ten years of research change using Google Trends: From the perspective of big data utilizations and applications. Technological forecasting and social change, 130, 69–87. JunS. P. YooH. S. ChoiS. 2018 Ten years of research change using Google Trends: From the perspective of big data utilizations and applications Technological forecasting and social change 130 69 87 Search in Google Scholar

Knobloch-Westerwick, S., Johnson, B. K., & Westerwick, A. (2014). Confirmation bias in online searches: Impacts of selective exposure before an election on political attitude strength and shifts. Journal of Computer-Mediated Communication, 20(2), 171–187. Knobloch-WesterwickS. JohnsonB. K. WesterwickA. 2014 Confirmation bias in online searches: Impacts of selective exposure before an election on political attitude strength and shifts Journal of Computer-Mediated Communication 20 2 171 187 Search in Google Scholar

Lorenz, E.N. (1963). Deterministic non-periodic flow. Journal of Atmospheric Sciences, 20, 130–41. LorenzE.N. 1963 Deterministic non-periodic flow Journal of Atmospheric Sciences 20 130 41 Search in Google Scholar

Mandelbrot, B. B. (1983) The fractal geometry of nature: Revised and enlarged edition. New York: WH Freeman and Co. MandelbrotB. B. 1983 The fractal geometry of nature: Revised and enlarged edition New York WH Freeman and Co. Search in Google Scholar

Magalhães, P. C. (2014). Introduction–financial crisis, austerity, and electoral politics. Journal of Elections, Public Opinion & Parties, 24(2), 125–133. MagalhãesP. C. 2014 Introduction–financial crisis, austerity, and electoral politics Journal of Elections, Public Opinion & Parties 24 2 125 133 Search in Google Scholar

Mellon, J. (2013). Where and when can we use Google Trends to measure issue salience?. PS: Political Science & Politics, 46(2), 280–290. MellonJ. 2013 Where and when can we use Google Trends to measure issue salience? PS: Political Science & Politics 46 2 280 290 Search in Google Scholar

Milan, S. (2015). Mobilizing in times of social media. From a politics of identity to a politics of visibility. In Critical Perspectives on Social Media and Protest (pp. 53–71), Rowman & Littlefield. MilanS. 2015 Mobilizing in times of social media. From a politics of identity to a politics of visibility In Critical Perspectives on Social Media and Protest 53 71 Rowman & Littlefield Search in Google Scholar

Mora Rodríguez, M., Flores Muñoz, F., & Valentinetti, D. (2021). Corporate impact of carbon disclosures: a nonlinear empirical approach. Journal of Financial Reporting and Accounting, 19(1), 4–27, in which the concept of structural breakpoint in time series analysis is highlighted. Mora RodríguezM. Flores MuñozF. ValentinettiD. 2021 Corporate impact of carbon disclosures: a nonlinear empirical approach Journal of Financial Reporting and Accounting 19 1 4 27 in which the concept of structural breakpoint in time series analysis is highlighted Search in Google Scholar

Olds, C. (2013). Assessing presidential agenda-setting capacity: dynamic comparisons of presidential, mass media, and public attention to economic issues. Congress & the Presidency, 40(3), 255–284. OldsC. 2013 Assessing presidential agenda-setting capacity: dynamic comparisons of presidential, mass media, and public attention to economic issues Congress & the Presidency 40 3 255 284 Search in Google Scholar

Reilly, S., Richey, S., & Taylor, J. B. (2012). Using google search data for state politics research: an empirical validity test using roll-off data. State Politics & Policy Quarterly, 12(2), 146–159 ReillyS. RicheyS. TaylorJ. B. 2012 Using google search data for state politics research: an empirical validity test using roll-off data State Politics & Policy Quarterly 12 2 146 159 Search in Google Scholar

Park, H. W. (2012). How do social scientists use link data from search engines to understand Internet-based political and electoral communication?. Quality & Quantity, 46(2), 679–693. ParkH. W. 2012 How do social scientists use link data from search engines to understand Internet-based political and electoral communication? Quality & Quantity 46 2 679 693 Search in Google Scholar

Serricchio, F., Tsakatika, M., & Quaglia, L. (2013). Euroscepticism and the global financial crisis. JCMS: Journal of Common Market Studies, 51(1), 51–64. SerricchioF. TsakatikaM. QuagliaL. 2013 Euroscepticism and the global financial crisis JCMS: Journal of Common Market Studies 51 1 51 64 Search in Google Scholar

Sowell, F. (1992). Maximum likelihood estimation of stationary univariate fractionally integrated time series models. Journal of Econometrics, 53(1–3), 165–188. SowellF. 1992 Maximum likelihood estimation of stationary univariate fractionally integrated time series models Journal of Econometrics 53 1–3 165 188 Search in Google Scholar

Urman, A., Makhortykh, M., & Ulloa, R. (2022). The matter of chance: auditing web search results related to the 2020 US presidential primary elections across six search engines. Social Science Computer Review, 40(5), 1323–1339. UrmanA. MakhortykhM. UlloaR. 2022 The matter of chance: auditing web search results related to the 2020 US presidential primary elections across six search engines Social Science Computer Review 40 5 1323 1339 Search in Google Scholar

Utych, S. M., & Kam, C. D. (2013). Viability, information seeking, and vote choice. The Journal of Politics, 76(1), 152–166. UtychS. M. KamC. D. 2013 Viability, information seeking, and vote choice The Journal of Politics 76 1 152 166 Search in Google Scholar

Wagner, K. M., & Gainous, J. (2009). Electronic grassroots: Does online campaigning work?. The Journal of Legislative Studies, 15(4), 502–520. WagnerK. M. GainousJ. 2009 Electronic grassroots: Does online campaigning work? The Journal of Legislative Studies 15 4 502 520 Search in Google Scholar

Yasseri, T., & Bright, J. (2014). Can electoral popularity be predicted using socially generated big data? it-Information Technology, 56(5), 246–253. YasseriT. BrightJ. 2014 Can electoral popularity be predicted using socially generated big data? it-Information Technology 56 5 246 253 Search in Google Scholar