Science and Technology Studies Commons^™

Yelp’S Review Filtering Algorithm, Yao Yao, Ivelin Angelov, Jack Rasmus-Vorrath, Mooyoung Lee, Daniel W. Engels

SMU Data Science Review

In this paper, we present an analysis of features influencing Yelp's proprietary review filtering algorithm. Classifying or misclassifying reviews as recommended or non-recommended affects average ratings, consumer decisions, and ultimately, business revenue. Our analysis involves systematically sampling and scraping Yelp restaurant reviews. Features are extracted from review metadata and engineered from metrics and scores generated using text classifiers and sentiment analysis. The coefficients of a multivariate logistic regression model were interpreted as quantifications of the relative importance of features in classifying reviews as recommended or non-recommended. The model classified review recommendations with an accuracy of 78%. We found that reviews …

Measuring Public Utilization Perception Potential Of Unmanned Aircraft Systems, Julius Keller, Daniel Kwasi Adjekum, Bortiorkor Nii Tsui Alabi, Brian Kozak

International Journal of Aviation, Aeronautics, and Aerospace

The integration of Unmanned Aircraft Systems (UAS) into the National Air Space (NAS) in recent times has been met by mixed public responses. The paper establishes four constructs each of which encapsulates multiple backgrounds and concerns of the stakeholders: functional knowledge, utilization trust, operational integration support, and safety risk-benefits. The paper hypothesizes that these constructs can serve as underlying components for a research instrument namely, the Public Utilization Perception Potential (PUPP) which can be used to assess the opinions of the public on UAS integration into NAS. Responses from the public on items in a beta-tested survey instrument were analyzed …

Models As Weapons: Review Of Weapons Of Math Destruction: How Big Data Increases Inequality And Threatens Democracy By Cathy O’Neil (2016), Samuel L. Tunstall

Numeracy

Cathy O’Neil. 2016. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (New York, NY: Crown) 272 pp. ISBN 978-0553418811.

Accessible to a wide readership, Cathy O’Neil’s Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy provides a lucid yet alarming account of the extensive reach of mathematical models in influencing all of our lives. With a particular eye towards social justice, O’Neil not only warns modelers to be cognizant of the effects of their work on real people—especially vulnerable groups who have less power to fight back—but also encourages laypersons to take initiative …