Social media has become a popular platform for people to share opinions. Among the social media mining research projects that study user opinions and issues, most focus on analyzing posted and shared content. They could run into the danger of non-representative findings as the opinions of users who do not post content are overlooked, which often happens in today's marketing, recommendation, and social sensing research. For a more complete and representative profiling of user opinions on various topical issues, we need to investigate the opinions of the users even when they stay silent on these issues. We call these users the issue specific-silent users (i-silent users). To study them and their opinions, we conduct an opinion survey on a set of users for two popular social media platforms, Twitter and Facebook. We further analyze their contributed personal social media data. Our main findings are that more than half of our users who are interested in issue i are i-silent users in Twitter. The same has been observed for our Facebook users. i-silent users are likely to have different opinion distribution from the users who post about i. With the ground truth user opinions from the survey, we further develop and apply opinion prediction methods to i-silent users in Twitter and Facebook using their social media data and their opinions on issues other than i.