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Revealing East Java Community Sentiments Towards Poverty: A Comparative Study Using LDA and BERT.

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Název: Revealing East Java Community Sentiments Towards Poverty: A Comparative Study Using LDA and BERT.
Autoři: Indriyanti, Aries Dwi, Gernowo, Rahmat, Sediyono, Eko
Zdroj: Cuestiones de Fisioterapia; 2025, Vol. 54 Issue 4, p7790-7801, 12p
Témata: SOCIAL media, LANGUAGE models, POVERTY reduction, SENTIMENT analysis, PUBLIC opinion
Abstrakt: Through sentiment analysis on the social media platform Twitter, this study explores public opinion on poverty issues in East Java, Indonesia. By understanding public perception, policymakers can develop more effective poverty alleviation strategies. By applying the BERT and LDA models, two dominant themes were identified: public concern about poverty conditions and social comparison between the rich and the poor. The BERT model achieved an accuracy of 75.6%, demonstrating the potential of social media analysis to understand public perception and inform effective poverty alleviation strategies. Despite achieving fairly good accuracy values, it should be noted that data limitations and sample representation may affect the generalizability of the study results. The results of this study indicate that sentiment analysis has significant potential in informing public policy, especially in the context of poverty alleviation. However, limitations such as data quality and representation need to be considered for future research. [ABSTRACT FROM AUTHOR]
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Databáze: Biomedical Index
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Abstrakt:Through sentiment analysis on the social media platform Twitter, this study explores public opinion on poverty issues in East Java, Indonesia. By understanding public perception, policymakers can develop more effective poverty alleviation strategies. By applying the BERT and LDA models, two dominant themes were identified: public concern about poverty conditions and social comparison between the rich and the poor. The BERT model achieved an accuracy of 75.6%, demonstrating the potential of social media analysis to understand public perception and inform effective poverty alleviation strategies. Despite achieving fairly good accuracy values, it should be noted that data limitations and sample representation may affect the generalizability of the study results. The results of this study indicate that sentiment analysis has significant potential in informing public policy, especially in the context of poverty alleviation. However, limitations such as data quality and representation need to be considered for future research. [ABSTRACT FROM AUTHOR]
ISSN:11358599