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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 501–525 of 630 papers

TitleStatusHype
Sentiment Analysis: A Survey—0
Sentiment Analysis in the News—0
Sentiment Analysis of Arabic Tweets Using Semantic Resources—0
Sentiment Analysis of German Twitter—0
Sentiment Analysis of Hindi Reviews based on Negation and Discourse Relation—0
Sentiment Analysis of Reviews: Should we analyze writer intentions or reader perceptions?—0
Sentiment Analysis of Tweets in Three Indian Languages—0
Sentiment Analysis of Twitter Data: A Survey of Techniques—0
Sentiment analysis on conversational texts—0
Sentiment Analysis on Customer Responses—0
Sentiment Analysis On Indian Indigenous Languages: A Review On Multilingual Opinion Mining—0
Sentiment analysis on Italian tweets—0
Sentiment Analysis on YouTube: A Brief Survey—0
Sentiment Analysis Using Collaborated Opinion Mining—0
Sentiment Analyzer with Rich Features for Ironic and Sarcastic Tweets—0
Sentiment and Belief: How to Think about, Represent, and Annotate Private States—0
Sentiment-Aspect Extraction based on Restricted Boltzmann Machines—0
Sentiment Classification in Swahili Language Using Multilingual BERT—0
Sentiment Classification of Arabic Documents: Experiments with multi-type features and ensemble algorithms—0
Sentiment Classification towards Question-Answering with Hierarchical Matching Network—0
Sentiment Lexicon Interpolation and Polarity Estimation of Objective and Out-Of-Vocabulary Words to Improve Sentiment Classification on Microblogging—0
SentiSys at SemEval-2016 Task 5: Opinion Target Extraction and Sentiment Polarity Detection—0
SentiTel: TABSA for Twitter reviews on Uganda Telecoms—0
Sentiue: Target and Aspect based Sentiment Analysis in SemEval-2015 Task 12—0
SI-LSTM: Speaker Hybrid Long-short Term Memory and Cross Modal Attention for Emotion Recognition in Conversation—0
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