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Online Platform Market Reputation Systems: Text Analytics and Machine Learning Approaches to Online Reputation - Softcover
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This research investigates the relationship among text review score, review length, agent behavior, and transfer-learning applications by constructing a quantitative measure with Airbnb online text reviews. The first essay focuses on studying the effects of review length on text review score. It constructs numerical text review scores by applying text analytics and machine learning techniques to more than three million user-generated text reviews on Airbnb. With the text review scores, this essay analyzes the impact of review length on text review scores and obtains insights on interplay relationship among text review score, review length, review age, and active reviewer. It finds an inverted U-shaped relation between review length and text review scores and a long-term downward trend of text review length cross all online platforms. This research contributes to online reputation field by building an innovative text review reputation measure and a large online labelled review corpus (i.e., Airbnb review knowledge base), investigating effects of review length on text review scores, and revealing a long-term trend of the online platform review length.
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Über die Autorin bzw. den Autor
Dr. Xiangming Samuel Li is a business professor at University Canada West and a PhD candidate in Management Sciences, University of Waterloo, Canada. He has received over 23 years of intensive management experiences in global ICT multinationals such as Nortel, Nokia, Motorola, Saveje, BTI, Anhub, and Linaro.
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Online Platform Market Reputation Systems
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This research investigates the relationship among text review score, review length, agent behavior, and transfer-learning applications by constructing a quantitative measure with Airbnb online text reviews. The first essay focuses on studying the effects of review length on text review score. It constructs numerical text review scores by applying text analytics and machine learning techniques to more than three million user-generated text reviews on Airbnb. With the text review scores, this essay analyzes the impact of review length on text review scores and obtains insights on interplay relationship among text review score, review length, review age, and active reviewer. It finds an inverted U-shaped relation between review length and text review scores and a long-term downward trend of text review length cross all online platforms. This research contributes to online reputation field by building an innovative text review reputation measure and a large online labelled review corpus (i.e., Airbnb review knowledge base), investigating effects of review length on text review scores, and revealing a long-term trend of the online platform review length. 60 pp. Englisch. Bestandsnummer des Verkäufers 9786138954545
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Online Platform Market Reputation Systems
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Li Xiangming SamuelDr. Xiangming Samuel Li is a business professor at University Canada West and a PhD candidate in Management Sciences, University of Waterloo, Canada. He has received over 23 years of intensive management experience. Bestandsnummer des Verkäufers 561877786
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Online Platform Market Reputation Systems
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This research investigates the relationship among text review score, review length, agent behavior, and transfer-learning applications by constructing a quantitative measure with Airbnb online text reviews. The first essay focuses on studying the effects of review length on text review score. It constructs numerical text review scores by applying text analytics and machine learning techniques to more than three million user-generated text reviews on Airbnb. With the text review scores, this essay analyzes the impact of review length on text review scores and obtains insights on interplay relationship among text review score, review length, review age, and active reviewer. It finds an inverted U-shaped relation between review length and text review scores and a long-term downward trend of text review length cross all online platforms. This research contributes to online reputation field by building an innovative text review reputation measure and a large online labelled review corpus (i.e., Airbnb review knowledge base), investigating effects of review length on text review scores, and revealing a long-term trend of the online platform review length.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch. Bestandsnummer des Verkäufers 9786138954545
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Online Platform Market Reputation Systems : Text Analytics and Machine Learning Approaches to Online Reputation
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This research investigates the relationship among text review score, review length, agent behavior, and transfer-learning applications by constructing a quantitative measure with Airbnb online text reviews. The first essay focuses on studying the effects of review length on text review score. It constructs numerical text review scores by applying text analytics and machine learning techniques to more than three million user-generated text reviews on Airbnb. With the text review scores, this essay analyzes the impact of review length on text review scores and obtains insights on interplay relationship among text review score, review length, review age, and active reviewer. It finds an inverted U-shaped relation between review length and text review scores and a long-term downward trend of text review length cross all online platforms. This research contributes to online reputation field by building an innovative text review reputation measure and a large online labelled review corpus (i.e., Airbnb review knowledge base), investigating effects of review length on text review scores, and revealing a long-term trend of the online platform review length. Bestandsnummer des Verkäufers 9786138954545
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Online Platform Market Reputation Systems | Text Analytics and Machine Learning Approaches to Online Reputation
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Taschenbuch. Zustand: Neu. Online Platform Market Reputation Systems | Text Analytics and Machine Learning Approaches to Online Reputation | Xiangming Samuel Li | Taschenbuch | Englisch | 2021 | Scholars' Press | EAN 9786138954545 | Verantwortliche Person für die EU: LAP Lambert Academic Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 120359361
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