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Sentiment Analysis: Mining Opinions, Sentiments, and Emotions
Social media online business text mining the fuzzy
2016/10/31
With the increasing development of Web 2.0, such as social media and online businesses,the need for perception of opinions, attitudes, and emotions grows rapidly. Sentiment analysis, the topic studyin...
Cross-lingual Sentiment Lexicon Learning With Bilingual Word Graph Label Propagation
Sentiment Lexicon Learning Bilingual Word Graph Label
2015/9/15
In this article we address the task of cross-lingual sentiment lexicon learning, which aims to automatically generate sentiment lexicons for the target languages with available English sentiment lexic...
A Statistical Parsing Framework for Sentiment Classification
Statistical Parsing Framework Sentiment Classification
2015/9/15
We present a statistical parsing framework for sentence-level sentiment classification in this article. Unlike previous works that use syntactic parsing results for sentiment analysis, we develop a st...
Bilingual Co-Training for Sentiment Classification of Chinese Product Reviews
Bilingual Co-Training Sentiment Classification Chinese Product
2015/9/9
The lack of reliable Chinese sentiment resources limits research progress on Chinese sentiment classification. However, there are many freely available English sentiment resources on the Web. This art...
We present a lexicon-based approach to extracting sentiment from text. The Semantic Orientation CALculator (SO-CAL) uses dictionaries of words annotated with their semantic orientation
(polarity and ...
More than Words:Syntactic Packaging and Implicit Sentiment
More than Words Syntactic Packaging Implicit Sentiment
2015/9/2
Work on sentiment analysis often focuses on the words and phrases that people use in overtly opinionated text. In this paper, we introduce a new approach to the problem that focuses not on lexical ind...
Unsupervised vector-based approaches to semantics can model rich lexical meanings, but they largely fail to capture sentiment information that is central to many word meanings and important for a wide...
Multi-Dimensional Sentiment Analysis with Learned Representations
Multi-Dimensional Sentiment Analysis Learned Representations
2015/6/15
Treating sentiment analysis as a classification problem has proven extremely useful, but it misses the blended, continuous nature of sentiment expression in natural language. Using data from the Exper...
Supplementary Material: Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
Recursive Deep Models Semantic Compositionality Sentiment Treebank
2015/6/15
This supplementary material contains four sections.The first section details the design and methods we used to create the Sentiment Treebank. The second provides an analysis of how much this treebank ...
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
Recursive Deep Models Semantic Compositionality Sentiment Treebank
2015/6/15
Semantic word spaces have been very useful but cannot express the meaning of longer phrases in a principled way. Further progress towards understanding compositionality in tasks such as sentiment dete...
Sentiment Expression Conditioned by Affective Transitions and Social Forces
Sentiment Expression Conditioned Affective Transitions Social Forces
2015/6/15
Human emotional states are not independent but rather proceed along systematic paths governed by both internal, cognitive factors and external, social ones. For example, anxiety often transitions to d...
Exploiting Social Network Structure for Person-to-Person Sentiment Analysis
Social Network Structure Person-to-Person Sentiment Analysis
2015/6/15
Person-to-person evaluations are prevalent in all kinds of discourse and important for establishing reputations, building social bonds,and shaping public opinion. Such evaluations can be analyzed sepa...
We introduce the idea of a sentiment summary, a single passage from a document that captures an author’s opinion about his or her subject. Using supervised data from the Rotten Tomatoes website, we ex...
Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions
Semi-Supervised Recursive Autoencoders Predicting Sentiment Distributions
2015/6/12
We introduce a novel machine learning framework based on recursive autoencoders for sentence-level prediction of sentiment label distributions. Our method learns vector space representations for multi...
Review Sentiment Scoring via a Parse-and-Paraphrase Paradigm
Parse-and-Paraphrase Paradigm Review Sentiment
2015/3/10
Review Sentiment Scoring via a Parse-and-Paraphrase Paradigm.