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Social and Behavioral Sciences Commons™
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Full-Text Articles in Social and Behavioral Sciences
Low Power Individuals In Social Power Research: A Quantitative Review, Theoretical Framework, And Empirical Test, Michael Schaerer, Christilene Du Plessis, Andy J. Yap, Stefan Thau
Low Power Individuals In Social Power Research: A Quantitative Review, Theoretical Framework, And Empirical Test, Michael Schaerer, Christilene Du Plessis, Andy J. Yap, Stefan Thau
Research Collection Lee Kong Chian School Of Business
We examine the role of low-power individuals in social power research. A multi-method literature review reveals that low-power individuals may be insufficiently understood because many studies lack necessary control conditions that allow drawing inferences about low power, effects are predominantly attributed to high power, and qualitative reviews primarily focus on how high-power individuals feel, think, and behave. Challenging the assumption that low power tends to produce opposite consequences of high power, we highlight several similarities between the two states. Based on social exchange theories, we propose that unequal-power (vs. equal-power) relationships make instrumental goals, competitive attitudes, and exchange rules salient, …
Yelp’S Review Filtering Algorithm, Yao Yao, Ivelin Angelov, Jack Rasmus-Vorrath, Mooyoung Lee, Daniel W. Engels
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 …
Study On Recovery Of Bad Social Media Reviews In The Hospitality Industry Using Project Management Principles, Franck Legrand
Study On Recovery Of Bad Social Media Reviews In The Hospitality Industry Using Project Management Principles, Franck Legrand
Dissertations and Theses
This research is about hotel guest recovery on social media. Whenever a guest has a bad experience during their stay, they share their opinion on social media. Negative reviews can damage hotel’s performance. This research seeks to gather information on the expectations of guest based on their personal experiences. Answering guests’ complaints on social media is a difficult task, as it requires an understanding of each guest personality traits. This thesis develops a methodology in order to understand the personality of guests, provide a clear response to answer the guests feedback on social media, help hotel managers to regain trust …