Opinion Mining
57 papers with code • 1 benchmarks • 10 datasets
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
Benchmarks
These leaderboards are used to track progress in Opinion Mining
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Datasets
IMDb Movie Reviews
MPQA Opinion Corpus
UR-FUNNY
MOS Dataset
Most implemented papers
Active learning in annotating micro-blogs dealing with e-reputation
This paper intends to develop a so-called active learning process for automatically annotating French language tweets that deal with the image (i. e., representation, web reputation) of politicians.
Towards Sub-Word Level Compositions for Sentiment Analysis of Hindi-English Code Mixed Text
We introduce a Hindi-English (Hi-En) code-mixed dataset for sentiment analysis and perform empirical analysis comparing the suitability and performance of various state-of-the-art SA methods in social media.
A Corpus of English-Hindi Code-Mixed Tweets for Sarcasm Detection
Social media platforms like twitter and facebook have be- come two of the largest mediums used by people to express their views to- wards different topics.
Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet Extraction
NKU-IIPLab/BMRC
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Aspect sentiment triplet extraction (ASTE), which aims to identify aspects from review sentences along with their corresponding opinion expressions and sentiments, is an emerging task in fine-grained opinion mining.
Representation learning for very short texts using weighted word embedding aggregation
Traditional textual representations, such as tf-idf, have difficulty grasping the semantic meaning of such texts, which is important in applications such as event detection, opinion mining, news recommendation, etc.
A domain-agnostic approach for opinion prediction on speech
We explore a domain-agnostic approach for analyzing speech with the goal of opinion prediction.
Replication issues in syntax-based aspect extraction for opinion mining
Reproducing experiments is an important instrument to validate previous work and build upon existing approaches.
Mining fine-grained opinions on closed captions of YouTube videos with an attention-RNN
These results, as well as further experiments on domain adaptation for aspect extraction, suggest that differences between speech and written text, which have been discussed extensively in the literature, also extend to the domain of product reviews, where they are relevant for fine-grained opinion mining.
