Web Analytics as a Preventative Tool:

Web analytics is moving forward in such a way that it could eventually flag “risky behaviors” in time to actually do something about them, like substance abuse” (Harris, 2012). The question within the industry is: Can online metrics and models be used to capture certain trends in order to maintain a better handle on them? The idea behind the method is if online metrics could be utilized to capture certain trends in order to get a better handle on them. Dr. Niranjan Karnik, associate professor of psychiatry and behavioral neuroscience at the University of Chicago stated: "If we can see the wave unfolding, we can launch a preventive effort" (Harris, 2012). One example would be software that could raise a flag when teens attempt to search online for instructions on how to extract alcohol from hand sanitizer. It could also submit a warning when a teenager searches for something like the “cinnamon challenge,” which has gained large popularity recently, but is actually quite dangerous. The Internet over the years has accelerated the process of word of mouth and is now “illuminating” these bad ideas and transforming them as trends. As Sidneyeve Matrix, a Queen’s University media professor, put it, "If we can see the wave unfolding, we can launch a preventive effort" (Harris, 2012). 

I think that online measurement tools like Web metrics could be quite useful to this generation. Some of the challenges are that the trends are fleeting and one may not have sufficient resources to be heard, like a vibrant community of parents, young people, doctors and educators. Another potential challenge for this idea is that the data does have the possibility of being skewed, as someone that may be searching for, the “cinnamon challenge” video, for instance, may not necessarily be interested in learning how to actually perform the activity, but is looking for it merely for entertainment purposes (Harris, 2012).

Google web search queries can already be used to accurately estimate influenza-like illness percentages in each of the public health regions of the United States. They present a method of analyze large numbers of Google search queries to track influenza-like illness within a population. Due to the quick processing rate of search queries, their estimates have consistently been 1-2 weeks ahead of CDC surveillance reports (Ginsberg, et. al, 2009). Early detection like this could eventually become a necessary and important defense against future epidemics in the U.S. and other countries as well. Their estimated will allows public health officials to better respond to seasonal epidemics and allot certain resources to specific regions to provide extra vaccine capacity or to raise the proper media awareness (Ginsberg, et. al, 2009). Utilizing the web metric search queries is not designed to replace traditional laboratory methods that are already in place, but to potentially indicate a need for public health inquiry to identify the pathogens involved. With this method, though, demographic data cannot be retrieved. It should also be known that although the correlations are strong from the users’ search queries, the system is still susceptible to false alerts that may be triggered by a random increase in Influenza-related queries. For instance, an unexpected and unusual event, like a drug recall for a widely-known cold or flu remedy could create this type of alert (Ginsberg, et. al, 2009).