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Paraskevas Koukaras, Dimitrios Rousidis and Christos Tjortjis
The identification and analysis of sentiment polarity in microblog data has drawn increased attention. Researchers and practitioners attempt to extract knowledge by evaluating public sentiment in response to global events. This study aimed to evaluate pu...
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Jie Zhao, Fangwei Xiong and Peiquan Jin
Microblogs are one of the major social networks in people?s daily life. The increasing amount of timely microblog data brings new opportunities for enterprises to predict short-term product sales based on microblogs because the daily microblogs posted by...
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Weijun Wang, Ying Li, Yinghui Huang, Hui Liu and Tingting Zhang
Analyzing people?s opinions, attitudes, sentiments, and emotions based on user-generated content (UGC) is feasible for identifying the psychological characteristics of social network users. However, most studies focus on identifying the sentiments carrie...
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Weijun Wang, Ying Li, Yinghui Huang, Hui Liu and Tingting Zhang
Analyzing people?s opinions, attitudes, sentiments, and emotions based on user-generated content (UGC) is feasible for identifying the psychological characteristics of social network users. However, most studies focus on identifying the sentiments carrie...
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Shangyi Yan, Jingya Wang and Zhiqiang Song
To address the shortcomings of existing deep learning models and the characteristics of microblog speech, we propose the DCCMM model to improve the effectiveness of microblog sentiment analysis. The model employs WOBERT Plus and ALBERT to dynamically enc...
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Yong Sun, Min Ji, Fengxiang Jin and Huimeng Wang
As air users, the public is also participants in air pollution control and important evaluators of environmental protection. Therefore, understanding the public perception and response to air pollution is an essential part of improving air governance. Th...
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