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Fine-Grained Opinion Analysis

Fine-Grained Opinion Analysis aims to: (i) detect opinion expressions that convey attitudes such as sentiments, agreements, beliefs, or intentions, (ii) measure their intensity, (iii) identify their holders i.e. entities that express an attitude, (iv) identify their targets i.e. entities or propositions at which the attitude is directed, and (v) classify their target-dependent attitude.

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Papers

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Showing 11–19 of 19 papers

TitleStatusHype
Relational Features in Fine-Grained Opinion Analysis—0
Syntax-Aware Opinion Role Labeling with Dependency Graph Convolutional Networks—0
The 2018 Shared Task on Extrinsic Parser Evaluation: On the Downstream Utility of English Universal Dependency Parsers—0
Toward Stance Classification Based on Claim Microstructures—0
Annotating Targets of Opinions in Arabic using Crowdsourcing—0
Why Words Alone Are Not Enough: Error Analysis of Lexicon-based Polarity Classifier for Czech—0
Extracting Opinion Expressions with semi-Markov Conditional Random Fields—0
Fine-Grained Opinion Summarization with Minimal Supervision—0
Investigating LSTMs for Joint Extraction of Opinion Entities and Relations—0
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