Abstract: Artificial intelligence technologies can effectively analyze the public opinions from social-media platforms like twitter. This study aims to employ the AI technology and big data to explore and discuss the common issues of asthma that patients share on Twitter platform in Arabic communities. The data was acquired using the Twitter API version 2. Latent Dirichlet Allocation was used for grouping data into two clusters which provide information and tips about the treatment and prevention of asthma and personal experiences with asthma, including symptoms, diagnosis, and the negative impact of asthma on the quality of life. Sentiment analysis and data frequency distribution techniques were used to analyze the data in both clusters. The data analysis of first indicated that individuals are interested in learning about different ways to treat asthma and potentially finding a permanent solution. The data analysis of second cluster indicated the existence of negative sentiments about asthma, which also included religious expressions for improving the condition. The study also discussed the differences in expressions among Arabic communities and other communities.

Mohammed Alotaibi and Ahmed Omar, “An Investigation of Asthma Experiences in Arabic Communities Through Twitter Discourse” International Journal of Advanced Computer Science and Applications(IJACSA), 14(5), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140549

@article{Alotaibi2023,
title = {An Investigation of Asthma Experiences in Arabic Communities Through Twitter Discourse},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140549},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140549},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {5},
author = {Mohammed Alotaibi and Ahmed Omar}
}