Social networking sites (SNS), such as Facebook and Twitter, are important spaces for political engagement. SNS have become common elements in political participation, campaigns, and elections. However, little is known about the dynamics between candidate posts and commentator sentiment in response to those posts on SNS. This study enriches computational political science by studying the 2016 U.S. elections and how candidates and commentators engage on Facebook. This paper also examines how online activity might be connected to offline activity and vice versa. We extracted 9,700 Facebook posts by five presidential candidates (Hillary Clinton, Donald Trump, Bernie Sanders, Ted Cruz, and John Kasich) from their official Facebook pages and 12,050,595 comments on those posts. We employed topic modeling, sentiment analysis, and trends detection using wavelet transforms to discover topics, trends, and reactions.