EXPRESS: Extremity Bias in Online Reviews: The Role of Attrition

2021 ◽  
pp. 002224372110735
Author(s):  
Leif Brandes ◽  
David Godes ◽  
Dina Mayzlin
Keyword(s):  
Large Scale ◽  
Heavy Tails ◽  
Online Reviews ◽  
Empirical Observation ◽  
Online Ratings ◽  
Large Scale Field ◽  
Theoretical Mechanism ◽  
Differential Utility ◽  
Online Travel ◽  
Extreme Distributions

In a range of studies across platforms, online ratings have been shown to be characterized by distributions with disproportionately-heavy tails. We focus on understanding the underlying process that yields such “j-shaped” or “extreme” distributions. We propose a novel theoretical mechanism behind the emergence of “j-shaped” distributions: differential attrition, or the idea that potential reviewers with moderate experiences are more likely to leave the pool of active reviewers than potential reviewers with extreme experiences. We present an analytical model that integrates this mechanism with two extant mechanisms: differential utility and base rates. We show that while all three mechanisms can give rise to extreme distributions, only the utility-based and the attrition-based mechanisms can explain our empirical observation from a large-scale field experiment that an unincentivized solicitation email from an online travel platform reduces review extremity. Subsequent analyses provide clear empirical evidence for the existence of both differential attrition and differential utility.

Investigate the Influence of Online Ratings and Reviews in Purchase Behavior Using Customer Choice Sets

2021 ◽  
Author(s):  
Kangcheng Lin ◽  
Harrison M. Kim
Keyword(s):  
Large Scale ◽  
Predictive Ability ◽  
Online Reviews ◽  
Purchase Behavior ◽  
Customer Choice ◽  
Product Demand ◽  
Average Rating ◽  
Online Ratings ◽  
The Impact ◽  
Choice Set

Abstract The exponentially growing online reviews have become a great wealth of information into which many researchers have started tapping. Using online reviews as a source of customer feedback, product designers are able to better understand customers’ preferences and improve product design accordingly. However, while predicting future product demand as a function of product attributes and customer heterogeneity has proved to be effective, not many literatures have studied the impact of non-product-related features, such as number of reviews and average ratings, on product demand using a large-scale dataset. As such, this paper proposes a data-driven methodology to investigate the influence of online ratings and reviews in purchase behavior by using discrete choice analysis. In the absence of information about the true customer choice set, we generate an estimated customer choice set based on a probability sampling using customer clustering and product clustering. In order to examine the effect of number of reviews and average rating, we have computed, for all the laptops in the choice set of each customer, the number of reviews and thus average rating at the date of this particular customer’s review. Using laptops for our case study, our experiment has shown that the number of reviews and average ratings are statistically significant, and the inclusion of these features will greatly improve the predictive ability of the model.

Biodata response elaboration: A large-scale field experiment

2010 ◽  
Author(s):  
Julia Levashina ◽  
Frederick P. Morgeson ◽  
Michael A. Campion
Keyword(s):  
Field Experiment ◽  
Large Scale ◽  
Scale Field ◽  
Large Scale Field

Hybrid Combination of GIS,GPS,WSN and GPRS Technology in Modern Digital Agriculture Application

2010 ◽  
Vol 108-111 ◽  
pp. 1158-1163 ◽  
Author(s):  
Peng Cheng Nie ◽  
Di Wu ◽  
Weiong Zhang ◽  
Yan Yang ◽  
Yong He
Keyword(s):  
Large Scale ◽  
Field Application ◽  
Wireless Sensor ◽  
Information Collection ◽  
Scale Field ◽  
Large Scale Field ◽  
Field Information ◽  
Intelligent Management ◽  
Digital Agriculture ◽  
And Control

In order to improve the information management of the modern digital agriculture, combined several modern digital agriculture technologies, namely wireless sensor network (WSN), global positioning system (GPS), geographic information system (GIS) and general packet radio service (GPRS), and applied them to the information collection and intelligent control process of the modern digital agriculture. Combining the advantage of the local multi-channel information collection and the low-power wireless transmission of WSN, the stable and low cost long-distance communication and data transmission ability of GPRS, the high-precision positioning technology of the DGPS positioning and the large-scale field information layer-management technology of GIS, such a hybrid technology combination is applied to the large-scale field information and intelligent management. In this study, wireless sensor network routing nodes are disposed in the sub-area of field. These nodes have GPS receiver modules and the electric control mechanism, and are relative positioned by GPS. They can real-time monitor the field information and control the equipment for the field application. When the GPS position information and other collected field information are measured, the information can be remotely transmitted to PC by GPRS. Then PC can upload the information to the GIS management software. All the field information can be classified into different layers in GIS and shown on the GIS map based on their GPS position. Moreover, we have developed remote control software based on GIS. It can send the control commands through GPRS to the nodes which have control modules; and then we can real-time manage and control the field application. In conclusion, the unattended automatic wireless intelligent technology for the field information collection and control can effectively utilize hardware resources, improve the field information intelligent management and reduce the information and intelligent cost.

scholarly journals Inverse Infiltration Modeling of Dike Covers Made of Dredged Material Using PEST and AMALGAM

Geosciences ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 41
Author(s):  
Tim Jurisch ◽  
Stefan Cantré ◽  
Fokke Saathoff
Keyword(s):  
Large Scale ◽  
Measurement Data ◽  
Fine Grained ◽  
Dredged Materials ◽  
Measurement Results ◽  
Large Scale Field ◽  
Eigenvalue Ratio ◽  
Ill Posed ◽  
Materials Used ◽  
Installation Technology

A variety of studies recently proved the applicability of different dried, fine-grained dredged materials as replacement material for erosion-resistant sea dike covers. In Rostock, Germany, a large-scale field experiment was conducted, in which different dredged materials were tested with regard to installation technology, stability, turf development, infiltration, and erosion resistance. The infiltration experiments to study the development of a seepage line in the dike body showed unexpected measurement results. Due to the high complexity of the problem, standard geo-hydraulic models proved to be unable to analyze these results. Therefore, different methods of inverse infiltration modeling were applied, such as the parameter estimation tool (PEST) and the AMALGAM algorithm. In the paper, the two approaches are compared and discussed. A sensitivity analysis proved the presumption of a non-linear model behavior for the infiltration problem and the Eigenvalue ratio indicates that the dike infiltration is an ill-posed problem. Although this complicates the inverse modeling (e.g., termination in local minima), parameter sets close to an optimum were found with both the PEST and the AMALGAM algorithms. Together with the field measurement data, this information supports the rating of the effective material properties of the applied dredged materials used as dike cover material.

scholarly journals On the dynamical interaction between overshooting convection and an underlying dipole magnetic field – I. The non-dynamo regime

2021 ◽  
Vol 503 (1) ◽  
pp. 362-375
Author(s):  
L Korre ◽  
NH Brummell ◽  
P Garaud ◽  
C Guervilly
Keyword(s):  
Magnetic Field ◽  
Turbulent Diffusion ◽  
Large Scale ◽  
Molecular Diffusion ◽  
Mean Field ◽  
Stable Region ◽  
Turbulent Regime ◽  
Poloidal Magnetic Field ◽  
Dynamical Interaction ◽  
Large Scale Field

ABSTRACT Motivated by the dynamics in the deep interiors of many stars, we study the interaction between overshooting convection and the large-scale poloidal fields residing in radiative zones. We have run a suite of 3D Boussinesq numerical calculations in a spherical shell that consists of a convection zone with an underlying stable region that initially compactly contains a dipole field. By varying the strength of the convective driving, we find that, in the less turbulent regime, convection acts as turbulent diffusion that removes the field faster than solely molecular diffusion would do. However, in the more turbulent regime, turbulent pumping becomes more efficient and partially counteracts turbulent diffusion, leading to a local accumulation of the field below the overshoot region. These simulations suggest that dipole fields might be confined in underlying stable regions by highly turbulent convective motions at stellar parameters. The confinement is of large-scale field in an average sense and we show that it is reasonably modelled by mean-field ideas. Our findings are particularly interesting for certain models of the Sun, which require a large-scale, poloidal magnetic field to be confined in the solar radiative zone in order to explain simultaneously the uniform rotation of the latter and the thinness of the solar tachocline.

Large scale field tests on geogrid-reinforced granular fill underlain by clay soil

2013 ◽  
Vol 38 ◽  
pp. 1-15 ◽  
Author(s):  
Ahmet Demir ◽  
Mustafa Laman ◽  
Abdulazim Yildiz ◽  
Murat Ornek
Keyword(s):  
Large Scale ◽  
Clay Soil ◽  
Field Tests ◽  
Scale Field ◽  
Granular Fill ◽  
Large Scale Field

scholarly journals Ethnic Discrimination in the Dutch Labor Market: Differences Between Ethnic Minority Groups and the Role of Personal Information About Job Applicants—Evidence from a Field Experiment

2020 ◽  
Author(s):  
Lex Thijssen ◽  
Marcel Coenders ◽  
Bram Lancee
Keyword(s):  
Labor Market ◽  
Field Experiment ◽  
Ethnic Minority ◽  
Large Scale ◽  
Minority Groups ◽  
Personal Information ◽  
Empirical Support ◽  
Ethnic Discrimination ◽  
Ethnic Minority Groups ◽  
Large Scale Field

AbstractIn this study, we present the results of a large-scale field experiment on ethnic discrimination in the Dutch labor market. We sent fictitious job applications (N = 4211) to vacancies for jobs in ten different occupations in the Netherlands. By examining 35 different ethnic minority groups, we detect considerable differences in discrimination rates, predominantly between Western and non-Western minorities. Furthermore, we find little systematic variation in discrimination patterns with regard to gender, regions, and occupations, pointing to the existence of an ethnic hierarchy that is widely shared among employers. Finally, we do not find empirical support for the hypothesis that adding personal information in job applications reduces discrimination.

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