Determining the Semantic Orientation of opinion words using typed dependencies for opinion word senses and Sentiwordnet scores from online product reviews

2017 ◽  
Vol 6 (2) ◽  
pp. 1
Author(s):  
K.C. Ravi Kumar ◽  
D. Teja Santosh ◽  
B. Vishnu Vardhan
Keyword(s):  
Product Reviews ◽  
Online Product Reviews ◽  
Semantic Orientation ◽  
Word Senses

Learned ontology guided opinions analysis of extracted aspects from online product reviews

2018 ◽  
Vol 51 (1-3) ◽  
pp. 25-49
Author(s):  
Ravi KUMAR ◽  
Teja SANTOSH DANDIBHOTLA ◽  
Vishnu VARDHAN BULUSU
Keyword(s):  
Product Reviews ◽  
Online Product Reviews

scholarly journals More Is Less: Only Moderate Polarized Online Product Reviews can Affect Sales

2018 ◽  
Vol 13 (4) ◽  
pp. 192 ◽  
Author(s):  
Li Yang
Keyword(s):  
Attribution Theory ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Research Question ◽  
Product Reviews ◽  
Online Product Reviews ◽  
Arousal Theory ◽  
Online Word Of Mouth ◽  
Analysis Technique ◽  
Product Sales

It is widely proved that positive online word-of-mouth (WOM) can boost sales and negative online WOM harm sales. Then will more positivity or negativity of messages in online product reviews text have greater impact on product sales? This research attempts to tackle this ignored research question. The answer is counter-intuitive: it depends on how positive or negative they are! The results of a two-way fixed-effects panel data analysis based on the data about tablet market in Amazon and a novel sentiment analysis technique demonstrate that the most and least polarized online product reviews actually have no effect on sales and only moderate positive / negative reviews can affect sales. Such effects can be explained by the optimal arousal theory and attribution theory. Inspired by the findings, three strategies for user-generated content (UGC) management are proposed.

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