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Social media plays a significant role in contemporary society and has become integral to daily life. This platform offers valuable insights for governments and stakeholders in advancing Smart City initiatives. One approach to harnessing social media data involves Sentiment Analysis, which categorizes text into various sentiments. It aid leaders in understanding public perceptions on specific topics. This study explores the relationship between Sentiment Analysis and six key domains of Smart City: Smart people, Smart economy, Smart governance, Smart mobility, Smart environment, and Smart living. Specifically focusing on the Smart economy domain, we utilize an English financial news Sentiment Analysis dataset, translate it into Persian, and evaluate a Persian Sentiment Analysis model. Our findings demonstrate the effectiveness of the tested Persian model in analyzing sentiment compared to English models, suggesting its applicability across other Smart City domains for Persian Language. (Abstract)
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Davoodian et al. (2024) studied this question.
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