IRAN Datasets

Citation Author(s):
Qiang
Lu
Shangdong Jiaotong university
Submitted by:
Qiang Lu
Last updated:
Tue, 05/17/2022 - 22:17
DOI:
10.21227/vsa7-ky18
Research Article Link:
Interactive Rule Attention Network for Aspect-Level Sentiment Analysis
License:
Creative Commons Attribution
235 Views
Categories:
Artificial Intelligence
Keywords:
Aspect-level sentiment analysis, grammatical rules, IRAN, interaction attention network
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Abstract 

We conduct experiments with the datasets of SemEval 2014 task4 to evaluate our model, the SemEval 2014 datasets consist of reviews in two categories: Restaurant and Laptop, and the reviews contains three labels of sentiment polarity: {positive, negative, neutral}

Instructions: 

The purpose of this annotation is to detect aspects and their sentiment polarity within

sentences. Sentences from customer reviews of restaurants and laptops will be used in this

task, i.e., the target entities will be particular restaurants or laptops. For a given target entity -

a restaurant or laptop-, the task of the annotator is to identify the following types of

information

Comments

Dataset needed for research purposes.

Submitted by Waleed Jadoon on Thu, 08/05/2021 - 00:47

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