Crowd-Squared: Amplifying the Predictive Power of Search Trend Data

Brynjolfsson, E., Geva, T., and Reichman, S. 2016. “Crowd-Squared: Amplifying the Predictive Power of Search Trend Data”, MIS Quarterly, Vol. 40 No. 4, pp. 941-961.

52 Pages Posted: 24 Oct 2014 Last revised: 28 Apr 2020

See all articles by Erik Brynjolfsson

Erik Brynjolfsson

Stanford; National Bureau of Economic Research (NBER)

Tomer Geva

Tel Aviv University

Shachar Reichman

Tel Aviv University - Coller School of Management; Massachusetts Institute of Technology (MIT) - Sloan School of Management

Date Written: November 10, 2015

Abstract

Big Data generated by crowds provides a myriad of opportunities for monitoring and modeling people's intentions, preferences, and opinions. A crucial step in analyzing such “big data” is selecting the relevant part of the data that should be provided as input to the modeling process. In this paper, we offer a novel, structured, crowd-based method to address the data selection problem in a widely used and challenging context: selecting search trend data. We label the method “crowd-squared,” as it leverages crowds to identify the most relevant terms in search volume data that were generated by a larger crowd. We empirically test this method in two domains and find that our method yields predictions that are equivalent or superior to those obtained in previous studies (using alternative data selection methods) and to predictions obtained using various benchmark data selection methods. These results emphasize the importance of a structured data selection method in the prediction process, and demonstrate the utility of the crowd-squared approach for addressing this problem in the context of prediction using search trend data.

Keywords: Prediction, Big Data, Search Trends, Data Selection, Crowdsourcing

Suggested Citation

Brynjolfsson, Erik and Geva, Tomer and Reichman, Shachar, Crowd-Squared: Amplifying the Predictive Power of Search Trend Data (November 10, 2015). Brynjolfsson, E., Geva, T., and Reichman, S. 2016. “Crowd-Squared: Amplifying the Predictive Power of Search Trend Data”, MIS Quarterly, Vol. 40 No. 4, pp. 941-961., Available at SSRN: https://ssrn.com/abstract=2513559. or http://dx.doi.org/10.2139/ssrn.2513559

Erik Brynjolfsson

Stanford ( email )

366 Galvez St
Stanford, CA 94305
United States

HOME PAGE: http://brynjolfsson.com

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Tomer Geva (Contact Author)

Tel Aviv University ( email )

Ramat Aviv
Tel-Aviv, 6997801
Israel

Shachar Reichman

Tel Aviv University - Coller School of Management ( email )

Tel Aviv
Israel

HOME PAGE: http://https://en-coller.tau.ac.il/profile/sr

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

77 Massachusetts Ave.
E62-412
Cambridge, MA 02142
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
1,210
Abstract Views
4,796
rank
20,363
PlumX Metrics