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- Citation Author(s):
- Submitted by:
- Qiang Lu
- Last updated:
- Tue, 05/17/2022 - 22:17
- DOI:
- 10.21227/vsa7-ky18
- Research Article Link:
- License:
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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.