Psychological Forest: Predicting Human Behavior

10 Pages Posted: 4 Aug 2016

See all articles by Ori Plonsky

Ori Plonsky

Technion-Israel Institute of Technology - The William Davidson Faculty of Industrial Engineering & Management

Ido Erev

Technion-Israel Institute of Technology - William Davidson Faculty of Industrial Engineering & Management

Tamir Hazan

Technion-Israel Institute of Technology

Moshe Tennenholtz

Technion-Israel Institute of Technology - The William Davidson Faculty of Industrial Engineering & Management

Date Written: May 19, 2016

Abstract

We introduce a synergetic approach incorporating psychological theories and machine learning in service of predicting human behavior. Our method harnesses fundamental psychological theories to provide rigorous features to a machine learning algorithm. We show that this approach can be extremely powerful. In particular, a random forest algorithm, dubbed psychological forest, which makes use of the psychological features in addition to the more standard objective and naive features, leads to prediction that significantly outperforms best practices in a choice prediction competition. Our results suggest that the main power of this synergy between psychological theories and machine learning is evident when facing a completely novel setting rather than completing missing values of a partially known matrix.

Suggested Citation

Plonsky, Ori and Erev, Ido and Hazan, Tamir and Tennenholtz, Moshe, Psychological Forest: Predicting Human Behavior (May 19, 2016). Available at SSRN: https://ssrn.com/abstract=2816450 or http://dx.doi.org/10.2139/ssrn.2816450

Ori Plonsky (Contact Author)

Technion-Israel Institute of Technology - The William Davidson Faculty of Industrial Engineering & Management ( email )

Haifa 32000
Israel

Ido Erev

Technion-Israel Institute of Technology - William Davidson Faculty of Industrial Engineering & Management ( email )

Haifa 32000
Israel

Tamir Hazan

Technion-Israel Institute of Technology ( email )

Technion City
Haifa 32000, Haifa 32000
Israel

Moshe Tennenholtz

Technion-Israel Institute of Technology - The William Davidson Faculty of Industrial Engineering & Management ( email )

Bloomfield-312
Haifa 32000
Israel
972-4-829 4419 (Phone)

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
211
Abstract Views
1,176
rank
151,965
PlumX Metrics