Worldwide, many people were shocked by the outcome of the U.S. presidential election of 2016. It’s been just over one full year since Trump’s electoral win and, although the race between Trump and Clinton was close, many of the electoral polls forecasted Clinton as the likely winner of the 2016 election (Perez, 2016). While the outcome of said election left many data scientists confused, many social media analytics firms are claiming that their measurements would have been a much better predictor (Perez, 2016).

If you are like me, you were one of those people shocked to hear Donald Trump won the American Presidential election. Chances are – also like me — you weren’t putting as much stock into the predictions of social media analysts as you were to major media outlets and traditional election polling firms. If we had been looking at the numbers and analytics we may have been better prepared. Phil Ross, a social media analyst at Socialbakers told Techcrunch.com “Analysts monitoring the social media activity of both campaigns on the major social media channels saw the outcome of this election coming months ago, and kept talking about the massive silent voter base that was forming around the Republican nominee. Social media analysts continually sounded the alarm that all of the polls were not reflecting the actual situation on the ground in the pre-election landscape.”

The media itself has been the news lately. The Trump campaign has made the press headline news. This conversation is not new. Since ancient Rome when important announcements were carved out on stone tablets and placed in busy squares, the public has measured the quality, delivery and merit of information/content. We are a society obsessed with being “in the loop” and up to date with news that is important to us. This is evidenced by the ubiquitous and near-constant use of electronic devices.  I chose The Hamilton Spectator, one of Canada’s oldest newspapers and media outlets, for this week’s case study. I wanted to know how TheSpec.com measures their performance using web and social media metrics.