Use Big Data to Predict Unemployment During the COVID-19 Pandemic

DOI

10.2991/978-94-6463-064-0_56How to use a DOI?

Keywords

Big Data; Unemployment; Google Trend Index; COVID-19

Abstract

Since the pandemic, unemployment has always been a concern in the United States. The aim of the paper is to use big data to predict unemployment in the U.S. Based on results from correlation matrix and OLS regression, I conclude that the Google Trend Index is a helpful reference to understand the situation of unemployment rate in every state in the United States. This paper contributes to the literature by connecting unemployment and Google Trend index at the state level, as well as providing a deep understanding of predicting economic factors using internet real-time big data.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Jamie Chen
PY  - 2022
DA  - 2022/12/27
TI  - Use Big Data to Predict Unemployment During the COVID-19 Pandemic
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
PB  - Atlantis Press
SP  - 545
EP  - 552
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-064-0_56
DO  - 10.2991/978-94-6463-064-0_56
ID  - Chen2022
ER  -