Literature DB >> 34899083

Augmenting Household Expenditure Forecasts with Online Employee-generated Company Reviews.

Efthymia Symitsi, Panagiotis Stamolampros, Antonios Karatzas.   

Abstract

We assess the ability of online employee-generated content in predicting consumption expenditures. In so doing, we aggregate millions of employee expectations for the next six-month business outlook of their employer and build an employee sentiment index. We test whether forward-looking employee sentiment can contribute to baseline models when forecasting aggregate consumption in the United States and compare its performance to well-established, survey-based consumer sentiment indexes. We reveal that online employee opinions have incremental information that can be used to augment the accuracy of consumption forecasting models and inform economic policy decisions.
© The Author(s) 2021. Published by Oxford University Press on behalf of American Association for Public Opinion Research.

Entities:  

Year:  2021        PMID: 34899083      PMCID: PMC8655719          DOI: 10.1093/poq/nfab017

Source DB:  PubMed          Journal:  Public Opin Q        ISSN: 0033-362X


  2 in total

1.  Social Media Analyses for Social Measurement.

Authors:  Michael F Schober; Josh Pasek; Lauren Guggenheim; Cliff Lampe; Frederick G Conrad
Journal:  Public Opin Q       Date:  2016-01-13

2.  Using Social Media for Actionable Disease Surveillance and Outbreak Management: A Systematic Literature Review.

Authors:  Lauren E Charles-Smith; Tera L Reynolds; Mark A Cameron; Mike Conway; Eric H Y Lau; Jennifer M Olsen; Julie A Pavlin; Mika Shigematsu; Laura C Streichert; Katie J Suda; Courtney D Corley
Journal:  PLoS One       Date:  2015-10-05       Impact factor: 3.240

  2 in total

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