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Pharmacol Res Perspect ; 8(5): e00640, 2020 10.
Article in English | MEDLINE | ID: mdl-32813329

ABSTRACT

Social media is playing an increasingly central role in patient's decision-making process. Advances in technology have enabled meaningful interpretation of discussions on social media. We conducted a scoping review to assess whether Sentiment Analysis (SA), a big data analytic tool, could be used to extract meaningful themes from social media discussions on pharmacotherapy. A keyword search strategy was used on the following databases: OneSearch, PubMed, Medline, EMBASE, and Cochrane. One hundred and ninety-four titles were identified of which 10 studies were included. We extracted themes about uses and implications of SA of social media discussions on pharmacotherapy. Twitter was the most frequently analyzed platform. Assessment of public sentiment about a particular medication was the most common use of SA followed by detection of adverse drug reactions. Studies also revealed a significant impact of news media on public sentiment. Implications for real world practice include identifying reasons for a negative sentiment, detecting adverse drug reactions and using the impact of news media on social media sentiment to drive public health initiatives. The lack of a consistent approach to SA between the studies reflects the lack of a gold standard for the technology and consequently the need for future research. Sentiment Analysis is a promising technology that can allow us to better understand patient opinion regarding pharmacotherapy. This knowledge can be used to improve patient safety, patient- physician interaction, and also enhance the delivery of public health measures.


Subject(s)
Data Mining/methods , Drug Therapy/psychology , Drug-Related Side Effects and Adverse Reactions/psychology , Big Data , Decision Making , Humans , Social Media
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