Sentiment Analysis of Animated Online Education Texts Using Long Short-Term Memory Networks in the Context of the Internet of Things-Reference-Cited by-同舟云学术

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Sentiment Analysis of Animated Online Education Texts Using Long Short-Term Memory Networks in the Context of the Internet of Things

Published:2023 Issue: Volume:11 Page:109121-109130
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Mao Jun¹,Qian Zhe²,Lucas Terry¹^ORCID

Affiliation:

1. Faculty of Applied and Creative Arts, Universiti Malaysia Sarawak, Kota Samarahan, Malaysia

2. College of Art Design, Hangzhou College of Commerce, Zhejiang Gongshang University, Hangzhou, China

Funder

Zhejiang Gongshang University, Hangzhou College of Commerce, Teaching Reform Research Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10268925.pdf?arnumber=10268925

Reference54 articles.

1. Prediction of Multi-Site PM2.5 Concentrations in Beijing Using CNN-Bi LSTM with CBAM

2. Effectiveness of the Use of Animation and Gamification in Online Distance Education During Pandemic

3. Sentiment analysis based on sentiment lexicon and stacked residual Bi-LSTM network;luo;J Comput Appl,2022

4. Temporal relative transformer encoding cooperating with channel attention for EEG emotion analysis

5. Accounting Information Quality, Financing Constraints, and Company Innovation Investment Efficiency by Big Data Analysis

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