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Fine-Grained Opinion Analysis

4 papers with code · 1 benchmark · 2 datasets archive 2025-07-28

Computer Vision Natural Language Processing

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.

( Image credit: SRL4ORL )

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Dataset	Best model (first row in archive order)	Paper	Code	Syntology	Compare
MPQA (3 rows)	SRL-SAWR	Enhancing Opinion Role Labeling with Semantic-Aware Word...	code	—	Compare

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

2 datasets whose archive record lists this task, ordered by the archive's paper count.

MPQA Opinion Corpus STATE ToxiCN

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Sentiment Analysis

Most implemented papers archive 2025-07-28

4 shown of 4 papers with code (19 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

Opinion Mining Using Pre-Trained Large Language Models: Identifying the Type, Polarity, Intensity, Expression, and Source of Private States

1 May 2024 1 repository listed

In this paper, we present a comprehensive study of the entire MPQA 2.
Mastering the Explicit Opinion-role Interaction: Syntax-aided Neural Transition System for Unified Opinion Role Labeling

5 Oct 2021 1 repository listed

Unified opinion role labeling (ORL) aims to detect all possible opinion structures of 'opinion-holder-target' in one shot, given a text.
Enhancing Opinion Role Labeling with Semantic-Aware Word Representations from Semantic Role Labeling

1 Jun 2019 1 repository listed

Opinion role labeling (ORL) is an important task for fine-grained opinion mining, which identifies important opinion arguments such as holder and target for a given opinion trigger.
SRL4ORL: Improving Opinion Role Labeling using Multi-task Learning with Semantic Role Labeling

2 Nov 2017 1 repository listed

For over a decade, machine learning has been used to extract opinion-holder-target structures from text to answer the question "Who expressed what kind of sentiment towards what?".

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