Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/29422
Title: | TaneNet: Two-Level Attention Network Based on Emojis for Sentiment Analysis |
Authors: | Zhao, Q Wu, P Lian, J An, D Li, M |
Keywords: | emojis;attention mechanisms;word embedding;sentiment analysis;neural network |
Issue Date: | 18-Jun-2024 |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Citation: | Zhao, Q. et al. (2024) 'TaneNet: Two-Level Attention Network Based on Emojis for Sentiment Analysis',IEEE Access, 12, pp. 86106 - 86119. doi: 10.1109/ACCESS.2024.3416379. |
Abstract: | During online communication, users often use irregular and ambiguous words, and sometimes use irony to express sarcasm. These words are difficult to analyze through text analysis, which poses a significant challenge for text sentiment analysis. As a novel communication method, emojis have a significant correlation with user emotions. In this paper, we use emojis to analyze the sentiment of short texts. Firstly, we validate that user information can help reduce the uncertainty of some emojis and use this information to identify the polarity of emojis. Then, we generate emoji representations by merging positional information, semantic information, emotional information, and frequency of appearance. Furthermore, we propose TaneNet, a two-level attention network based on emojis, which combines clause vectors and emoji representations to study the impact of emojis on the emotions of each clause in the text. Empirical results on two real-world datasets demonstrate that TaneNet outperforms existing state-of-the-art methods |
URI: | https://bura.brunel.ac.uk/handle/2438/29422 |
DOI: | https://doi.org/10.1109/ACCESS.2024.3416379 |
Other Identifiers: | ORCiD: Qin Zhao https://orcid.org/0000-0001-7579-2004 ORCiD: Jie Lian https://orcid.org/0000-0002-2005-2022 ORCiD: Dongdong An https://orcid.org/0000-0002-1412-8182 ORCiD: Mazhen Li https://orcid.org/0000-0002-0820-5487 |
Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
FullText.pdf | Copyright © 2024 The Authors. Published by Institute of Electrical and Electronics Engineers (IEEE). This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/ | 1.35 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License