| Abstrak/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, retweet, 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 |
