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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Nowcasting Unemployment Rates with Google Searches: Evidence from the Visegrad Group Countries
Jaroslav Pavlíček, Ladislav Krištoufek
PLoS ONE (2015) Vol. 10, Iss. 5, pp. e0127084-e0127084
Open Access | Times Cited: 60

Showing 1-25 of 60 citing articles:

Computational socioeconomics
Jian Gao, Yi‐Cheng Zhang, Tao Zhou
Physics Reports (2019) Vol. 817, pp. 1-104
Open Access | Times Cited: 100
Winners and Losers from COVID-19: Global Evidence from Google Search
Kibrom A. Abay, Kibrom Tafere, Andinet Woldemichael
World Bank, Washington, DC eBooks (2020)
Open Access | Times Cited: 88
Big Data: Potential, Challenges and Statistical Implications
Cornelia Hammer, Diane C Kostroch, Gabriel Pérez‐Quirós
IMF staff discussion note (2017) Vol. 17, Iss. 06, pp. 1-1
Open Access | Times Cited: 64
Improving unemployment rate forecasts at regional level in Romania using Google Trends
Simionescu Mihaela
Technological Forecasting and Social Change (2020) Vol. 155, pp. 120026-120026
Closed Access | Times Cited: 49
Time series prediction of under-five mortality rates for Nigeria: comparative analysis of artificial neural networks, Holt-Winters exponential smoothing and autoregressive integrated moving average models
Daniel A. Adeyinka, Nazeem Muhajarine
BMC Medical Research Methodology (2020) Vol. 20, Iss. 1
Open Access | Times Cited: 39
Using four different online media sources to forecast the crude oil price
Mohammed Elshendy, Andrea Fronzetti Colladon, Elisa Battistoni, et al.
Journal of Information Science (2017) Vol. 44, Iss. 3, pp. 408-421
Closed Access | Times Cited: 39
A Machine Learning Approach for Detecting Unemployment Using the Smart Metering Infrastructure
Casimiro Curbelo Montañez, William Hurst
IEEE Access (2020) Vol. 8, pp. 22525-22536
Open Access | Times Cited: 24
A bridge between sentiment indicators: What does Google Trends tell us about COVID-19 pandemic and employment expectations in the EU new member states?
Mihaela Simionescu, Agota Giedrė Raišienė
Technological Forecasting and Social Change (2021) Vol. 173, pp. 121170-121170
Open Access | Times Cited: 22
Forecasting Spanish unemployment with Google Trends and dimension reduction techniques
Rodrigo Mulero, Alfredo García‐Hiernaux
SERIEs (2021) Vol. 12, Iss. 3, pp. 329-349
Open Access | Times Cited: 21
A Model Selection Approach for Time Series Forecasting: Incorporating Google Trends Data in Australian Macro Indicators
Ali Abdul Karim, Eric Pardede, Scott Mann
Entropy (2023) Vol. 25, Iss. 8, pp. 1144-1144
Open Access | Times Cited: 8
The Detection of Emerging Trends Using Wikipedia Traffic Data and Context Networks
Mirko Kämpf, Eric Tessenow, Dror Y. Kenett, et al.
PLoS ONE (2015) Vol. 10, Iss. 12, pp. e0141892-e0141892
Open Access | Times Cited: 27
Measuring Employment Demand Using Internet Search Data
Stevie Chancellor, Scott Counts
(2018), pp. 1-14
Closed Access | Times Cited: 21
Race, religion and the city: twitter word frequency patterns reveal dominant demographic dimensions in the United States
Eszter Bokányi, Dániel Kondor, László Dobos, et al.
Palgrave Communications (2016) Vol. 2, Iss. 1
Open Access | Times Cited: 21
USING BAIDU INDEX TO NOWCAST MOBILE PHONE SALES IN CHINA
Jianchun Fang, Wanshan Wu, Zhou Lu, et al.
The Singapore Economic Review (2017) Vol. 64, Iss. 01, pp. 83-96
Closed Access | Times Cited: 20
Prediction of employment and unemployment rates from Twitter daily rhythms in the US
Eszter Bokányi, Zoltán Lábszki, Gábor Vattay
EPJ Data Science (2017) Vol. 6, Iss. 1
Open Access | Times Cited: 17
How do Google searches for symptoms, news and unemployment interact during COVID-19? A Lotka–Volterra analysis of google trends data
Chiara Sotis
Quality & Quantity (2021) Vol. 55, Iss. 6, pp. 2001-2016
Open Access | Times Cited: 14
Using digital technologies to improve the design and enforcement of public policies
OECD
OECD digital economy papers (2019)
Open Access | Times Cited: 14
A method for measuring detailed demand for workers’ competences
Robert Pater, Jarosław Szkoła, Marcin Kozak
Economics (2019) Vol. 13, Iss. 1
Open Access | Times Cited: 13
Forecasting U.S. Domestic Migration Using Internet Search Queries
Allen Yilun Lin, Justin Cranshaw, Scott Counts
(2019), pp. 1061-1072
Closed Access | Times Cited: 13
Revisiting the use of web search data for stock market movements
Xu Zhong, Michael Raghib
Scientific Reports (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 12
Real-time nowcasting the monthly unemployment rates with daily Google Trends data
Eduardo Costa, Maria Eduarda Silva, Ana Beatriz Galvão
Socio-Economic Planning Sciences (2024) Vol. 95, pp. 101963-101963
Open Access | Times Cited: 1
COVID-19 and the intentions to migrate from developing countries: Evidence from online search activities in Southeast Asia
Nobuyuki Nakamura, Aya Suzuki
Journal of Asian Economics (2021) Vol. 76, pp. 101348-101348
Open Access | Times Cited: 10
Forecasting unemployment with Google Trends: age, gender and digital divide
Rodrigo Mulero, Alfredo García‐Hiernaux
Empirical Economics (2022) Vol. 65, Iss. 2, pp. 587-605
Open Access | Times Cited: 7
Nowcasting Unemployment Rates with Smartphone GPS Data
Daisuke Moriwaki
Lecture notes in computer science (2020), pp. 21-33
Open Access | Times Cited: 10
In search of art: rapid estimates of gallery and museum visits using Google Trends
Federico Botta, Tobias Preis, Helen Susannah Moat
EPJ Data Science (2020) Vol. 9, Iss. 1
Open Access | Times Cited: 10
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