  Adverse reactions caused by drugs following their release into the market are
among the leading causes of death in many countries. The rapid growth of
electronically available health related information, and the ability to process
large volumes of them automatically, using natural language processing (NLP)
and machine learning algorithms, have opened new opportunities for
pharmacovigilance. Survey found that more than 70% of US Internet users consult
the Internet when they require medical information. In recent years, research
in this area has addressed for Adverse Drug Reaction (ADR) pharmacovigilance
using social media, mainly Twitter and medical forums and websites. This paper
will show the information which can be collected from a variety of Internet
data sources and search engines, mainly Google Trends and Google Correlate.
While considering the case study of two popular Major depressive Disorder (MDD)
drugs, Duloxetine and Venlafaxine, we will provide a comparative analysis for
their reactions using publicly-available alternative data sources.
