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Opinion Mining

Identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer's attitude towards a particular topic, product, etc. is positive, negative, or neutral (Source: Oxford Languages)

Image Source: Deep learning for sentiment analysis: A survey

Papers

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Showing 326–350 of 630 papers

TitleStatusHype
Lexical Based Semantic Orientation of Online Customer Reviews and Blogs—0
Representation learning for very short texts using weighted word embedding aggregationCode0
IIT-TUDA at SemEval-2016 Task 5: Beyond Sentiment Lexicon: Combining Domain Dependency and Distributional Semantics Features for Aspect Based Sentiment Analysis—0
Trainable Citation-enhanced Summarization of Scientific Articles—0
Implicit Aspect Detection in Restaurant Reviews using Cooccurence of Words—0
INF-UFRGS-OPINION-MINING at SemEval-2016 Task 6: Automatic Generation of a Training Corpus for Unsupervised Identification of Stance in Tweets—0
DSIC-ELIRF at SemEval-2016 Task 4: Message Polarity Classification in Twitter using a Support Vector Machine Approach—0
JU\_NLP at SemEval-2016 Task 6: Detecting Stance in Tweets using Support Vector Machines—0
TGB at SemEval-2016 Task 5: Multi-Lingual Constraint System for Aspect Based Sentiment Analysis—0
AUEB-ABSA at SemEval-2016 Task 5: Ensembles of Classifiers and Embeddings for Aspect Based Sentiment Analysis—0
LyS at SemEval-2016 Task 4: Exploiting Neural Activation Values for Twitter Sentiment Classification and Quantification—0
Making Sense of Massive Amounts of Scientific Publications: the Scientific Knowledge Miner Project—0
MDSENT at SemEval-2016 Task 4: A Supervised System for Message Polarity Classification—0
Classification of comment helpfulness to improve knowledge sharing among medical practitioners.—0
BUTknot at SemEval-2016 Task 5: Supervised Machine Learning with Term Substitution Approach in Aspect Category Detection—0
NLANGP at SemEval-2016 Task 5: Improving Aspect Based Sentiment Analysis using Neural Network Features—0
UWB at SemEval-2016 Task 6: Stance Detection—0
NRU-HSE at SemEval-2016 Task 4: Comparative Analysis of Two Iterative Methods Using Quantification Library—0
UWB at SemEval-2016 Task 7: Novel Method for Automatic Sentiment Intensity Determination—0
SentiSys at SemEval-2016 Task 5: Opinion Target Extraction and Sentiment Polarity Detection—0
PotTS at SemEval-2016 Task 4: Sentiment Analysis of Twitter Using Character-level Convolutional Neural Networks.—0
Tweester at SemEval-2016 Task 4: Sentiment Analysis in Twitter Using Semantic-Affective Model Adaptation—0
Using Data Mining Techniques for Sentiment Shifter Identification—0
DRANZIERA: An Evaluation Protocol For Multi-Domain Opinion Mining—0
Online shopping behavior study based on multi-granularity opinion mining: China vs. America—0
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