Public Perspective on Hyperlipidemia Drugs and Sentiments About Hyperlipidemia on Twitter

Murojil Hasan, Chairun Wiedyaningsih, Nanang Munif Yasin
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Abstract

Hyperlipidemia is a non-communicable disease (NCD) caused by several factors, such as a person's socioeconomic status, culture, customs, habits, and lifestyle. Through user interaction on social media, we can discover the model anti-hyperlipidemia by extracting information, complaints, suggestions, and calls for help about the treatment, which will play a role as an intervention to reduce hyperlipidemia in Indonesia. This study aimed to identify factors influencing perceptions of hyperlipidemia drugs and resulting sentiment on the social media platform Twitter. This study used user-uploaded tweet data to compare perceptions of hyperlipidemia drugs in 2020 and keywords for hyperlipidemia terms and medicine. Tweets related to anti-hyperlipidemia were extracted by issuing tweets containing advertisements, news, re-tweet, and content outside of health. The tweet data obtained was then carried out through content analysis, including point of view, theme, and sentiment analysis, to identify whether the resulting tweets are positive, neutral, or negative using the Support Vector Machine (SVM) method. We identified 1572 hyperlipidemia-related tweets and 153 specific tweets describing hyperlipidemia medications. Tweets about anti-hyperlipidemia showed 99 tweets from the first-person perspective, 23 from the second-person perspective, 22 from healthcare professionals, and nine unidentifiable (other). Sixty-three tweets talked about the benefits of lipid-lowering drugs, 17 complaint tweets, 49 suggestion tweets, 17 question tweets, and two side effect tweets. Assessing public perceptions and sentiment toward hyperlipidemia treatment can be used to develop strategies to increase treatment adherence, improve treatment outcomes, and target health promotion efforts.
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公众对高脂血症药物的看法和Twitter上对高脂血症的看法
高脂血症是一种由多种因素引起的非传染性疾病(NCD),如一个人的社会经济地位、文化、习俗、习惯和生活方式。通过在社交媒体上的用户互动,我们可以通过提取治疗信息、投诉、建议、求助来发现抗高脂血症模型,从而起到干预印尼降低高脂血症的作用。这项研究旨在确定影响高脂血症药物认知的因素,以及社交媒体平台Twitter上的情绪。这项研究使用用户上传的推特数据来比较2020年对高脂血症药物的看法以及高脂血症术语和药物的关键词。通过发布包含广告、新闻、转发和健康以外内容的推文提取与抗高脂血症相关的推文。然后对得到的推文数据进行内容分析,包括观点分析、主题分析、情感分析,利用支持向量机(Support Vector Machine, SVM)方法识别得到的推文是积极、中性还是消极。我们确定了1572条与高脂血症相关的推文和153条描述高脂血症药物的特定推文。关于抗高脂血症的推文显示,99条推文是第一人称视角,23条是第二人称视角,22条是医疗专业人士,9条是无法识别的(其他)。63条推文谈论降脂药物的好处,17条抱怨推文,49条建议推文,17条问题推文,以及2条副作用推文。评估公众对高脂血症治疗的看法和情绪可用于制定策略,以增加治疗依从性,改善治疗结果,目标健康促进工作。
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