Emotion analysis of teaching evaluation system based on AI techno-logy towards Chinese texts

Dandan, Hong; Gao, Zhan; Luo, Jie; Jun, Liu; Xu, Man; Suo, Zhihai; Ji, Xiangting

doi:10.1051/matecconf/202133605007

Cited by 6 publications

(1 citation statement)

References 3 publications

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“…Many studies adopted the sentiment expressed in tweets created/retweeted/commented by users to represent their attitudes toward vaccines [ 5 , 20 , 57 ]. Considering the Chinese context of Weibo [ 58 ], we used Baidu’s AipNLP [ 59 ] to calculate the sentimental positive probability (0≤α≤1) of each original tweet, retweet, and comment. If 0≤α≤0.5, the text was regarded as negative; if 0<α≤1, the text was regard as positive; and otherwise, it was regard as neutral.…”

Section: Methodsmentioning

confidence: 99%

Opinion Leaders and Structural Hole Spanners Influencing Echo Chambers in Discussions About COVID-19 Vaccines on Social Media in China: Network Analysis

Wang

Zhou

2022

J Med Internet Res

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Background Social media provide an ideal medium for breeding and reinforcing vaccine hesitancy, especially during public health emergencies. Algorithmic recommendation–based technology along with users’ selective exposure and group pressure lead to online echo chambers, causing inefficiency in vaccination promotion. Avoiding or breaking echo chambers largely relies on key users’ behavior. Objective With the ultimate goal of eliminating the impact of echo chambers related to vaccine hesitancy on social media during public health emergencies, the aim of this study was to develop a framework to quantify the echo chamber effect in users’ topic selection and attitude contagion about COVID-19 vaccines or vaccinations; detect online opinion leaders and structural hole spanners based on network attributes; and explore the relationships of their behavior patterns and network locations, as well as the relationships of network locations and impact on topic-based and attitude-based echo chambers. Methods We called the Sina Weibo application programming interface to crawl tweets related to the COVID-19 vaccine or vaccination and user information on Weibo, a Chinese social media platform. Adopting social network analysis, we examined the low echo chamber effect based on topics in representational networks of information, according to attitude in communication flow networks of users under different interactive mechanisms (retweeting, commenting). Statistical and visual analyses were used to characterize behavior patterns of key users (opinion leaders, structural hole spanners), and to explore their function in avoiding or breaking topic-based and attitude-based echo chambers. Results Users showed a low echo chamber effect in vaccine-related topic selection and attitude interaction. For the former, the homophily was more obvious in retweeting than in commenting, whereas the opposite trend was found for the latter. Speakers, replicators, and monologists tended to be opinion leaders, whereas common users, retweeters, and networkers tended to be structural hole spanners. Both leaders and spanners tended to be “bridgers” to disseminate diverse topics and communicate with users holding cross-cutting attitudes toward COVID-19 vaccines. Moreover, users who tended to echo a single topic could bridge multiple attitudes, while users who focused on diverse topics also tended to serve as bridgers for different attitudes. Conclusions This study not only revealed a low echo chamber effect in vaccine hesitancy, but further elucidated the underlying reasons from the perspective of users, offering insights for research about the form, degree, and formation of echo chambers, along with depolarization, social capital, stakeholder theory, user portraits, dissemination pattern of topic, and sentiment. Therefore, this work can help to provide strategies for public health and public opinion managers to cooperate toward avoiding or correcting echo chamber chaos and effectively promoting online vaccine campaigns.

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Section: Methodsmentioning

confidence: 99%

Opinion Leaders and Structural Hole Spanners Influencing Echo Chambers in Discussions About COVID-19 Vaccines on Social Media in China: Network Analysis

Wang

Zhou

2022

J Med Internet Res

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Effect Evaluation of Online Basic Japanese Lessons Based on Data Mining Algorithm

Wang

Feng

2022

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Evaluation of English Teaching Quality in Higher Vocational Colleges Based on Artificial Intelligence Optimization Network

Zhang

2023

Application of Big Data, Blockchain, and Internet of Things for Education Informatization

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Emotion analysis of teaching evaluation system based on AI techno-logy towards Chinese texts

Cited by 6 publications

References 3 publications

Opinion Leaders and Structural Hole Spanners Influencing Echo Chambers in Discussions About COVID-19 Vaccines on Social Media in China: Network Analysis

Opinion Leaders and Structural Hole Spanners Influencing Echo Chambers in Discussions About COVID-19 Vaccines on Social Media in China: Network Analysis

Effect Evaluation of Online Basic Japanese Lessons Based on Data Mining Algorithm

Evaluation of English Teaching Quality in Higher Vocational Colleges Based on Artificial Intelligence Optimization Network

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