社会化媒体
2019年冠状病毒病(COVID-19)
情感(语言学)
心理学
情绪分析
情绪检测
计算机科学
社会学
数据科学
人工智能
万维网
情绪识别
医学
沟通
疾病
病理
传染病(医学专业)
作者
Ehsan Dorostkar,Mahsa Najarsadeghi
出处
期刊:Cities
[Elsevier BV]
日期:2022-05-30
卷期号:127: 103713-103713
被引量:16
标识
DOI:10.1016/j.cities.2022.103713
摘要
Unstructured data on social media can be used to develop urban planning knowledge. The emotions created by social media can positively or negatively affect the community. The purpose of this study is to develop artificial intelligence models in urban analysis to discover emotions on Twitter social media in Tehran. By referring to the API, we extracted the tweets related to the Covid 19 and explored the data in the period 3/2020 to 9/2020 for Tehran. After analyzing and classifying the created emotions, prepared time series. Finally, we found that the published tweets have a strong reaction to the Covid 19 in 4 sections. With the onset of the epidemic, one of these reactions has had a widespread negative impact on Twitter, provoking urban emotions. The other 3 reactions, made small and cross-sectional effects and decreased with the decline of the epidemic peak.
科研通智能强力驱动
Strongly Powered by AbleSci AI