Identifying Structural Holes for Sentiment Classification
Abstract
The prevalence of online user-generated content has attracted great interest in textual sentiment analysis, which provides a low-cost yet effective way to discern consumers and markets. A mainstream of sentiment analysis is to construct a classification model with Bag-of-Words (BoW) features, but the large vocabulary base and skewed distribution of term frequency consistently pose research challenges, which is made even worse by the limited...
Paper Details
Title
Identifying Structural Holes for Sentiment Classification
Published Date
Sep 1, 2021
Volume
24
Issue
5
Pages
1735 - 1751
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