Exploring adverse drug reactions of diabetes medicine using social media analytics and interactive visualizations

Si Li, Chia-Hui Yu, Yichuan Wang and Yedurag Babu

International Journal of Information Management, 2019, vol. 48, issue C, 228-237

Abstract: The aim of this study is to propose an automatic and real-time social media analytics framework with interactive data visualizations to support effective exploration of knowledge about adverse drug reaction (ADR) surveillance. This proposed framework has been prototypically implemented on the basis of social media data. A longitudinal diabetes patient online community data (AskaPatient.com) as well as FDA Adverse Event Reporting Systems (FAERS) data as a benchmark were used to evaluate our proposed approach’s performance. Based on the results, our approach significantly increases the precision and accuracy for ADR extraction. The number of ADR cases, the time when the ADRs occurred, and the rating of Glucophage have been visualized that resulted by mining a collection of 870 ADRs posted in Askapatents.com over a certain time period (from 2001 to 2015). The results have important implications for pharmaceutical companies and hospitals wishing to monitor ADRs of medicines.

Keywords: Social media analytics; Adverse drug reactions (ADRs); Data visualization; Big data analytics; Online health community (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ininma:v:48:y:2019:i:c:p:228-237

DOI: 10.1016/j.ijinfomgt.2018.12.007

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