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International Journal of Bio-Science and Bio-Technology

Volume 9, No. 5, 2017, pp 13-24
http://dx.doi.org/10.21742/ijbsbt.2017.9.5.02

Abstract



Big Data Analytics Approach for Evaluating Antihypertension Medications’ Usage from Online Patient Care Blogs



    Nil Shah1, Jinan Fiaidhi and Sabah Mohammed
    Department of Computer Science, Lakehead University, ON, Canada

    Abstract

    Throughout history, the area of drug discovery and development has been a financial strain due to the associated high costs. In order to offset this financial burden, drug companies are continually increasing the price of medications to consumers. Some consumers remain unaware of the types of medications available on the market and the gap in cost between these types. The two main types of medications available on the market are: 1) Generic drugs and 2) Brand name drugs. The purpose of this paper is to examine the similarities and difference of generic and brand name drugs from patient’s reviews at major medications blogs like dugs.com. A subjectivity sentimental analysis framework has been developed that can effectively score these reviews without going into the complexities of using natural language or machine learning approaches. The developed framework use a well-known rule based subjectivity API known as VADER besides an effective web crawler. Results of this analysis shows more sentiments are with the generic antihypertension drugs compared to the brand drugs. The validation of these results was based on Google Trends. More concrete analysis of the results on wider list of medications as well as more blogs is left to our future work.


 

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