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- W3203339364 abstract "Social networking sites have been a common forum for exchanging health-related insights and information. This study aims to look at Twitter use in the intervention of diabetes. Specifically, utilizing a prior analysis as a reference, we use a revised approach to analyse trends in the existing use of hash-tags, trending hash-tags, and the incidence of diabetes-related tweets. Our findings indicate that the diabetes population on Twitter has grown significantly over time, as well as proof that this community is becoming more capable of spreading diabetes-related health information. An enhanced system for storing, cleaning, and reviewing Twitter data relevant to diabetes, as well as the use of regular expressions to categorize subsets of tweets, are among our computational contributions. To recognize tweets from diabetic patients, we built a model focused on word embedding and long short- term memory. Based on our findings, our model is working well, since the term embedded with the LSTM classifiers." @default.
- W3203339364 created "2021-10-11" @default.
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- W3203339364 date "2021-07-09" @default.
- W3203339364 modified "2023-09-24" @default.
- W3203339364 title "Usage of social media Twitter in the Intervention of Diabetes Mellitus" @default.
- W3203339364 doi "https://doi.org/10.52152/spr/2021.119" @default.
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