In the current digital age, we see that reviews from social networks or microblogging significantly influence one’s decision-making. It has been observed that a large number of reviews and comments regarding educational institutions are placed on these sites. As we all know, many new platforms have been formed over time, increasing the activity of users to voice their opinions on these platforms. As a result, users, particularly students, are more likely to become perplexed while trying to conclude. To address this issue, this paper looks at the analysis of a few platforms as a source of getting the reviews/comments of Universities, and with the help of sentiment analysis, we get an overview of a specific universities’ position in the market, which includes certain parameters such as quality of faculty, mess, infrastructure and so on. For this purpose, first, the reviews from known platforms are collected and then they are classified into a few categories like good, average, below average, and bad. At last, the results are shown in terms of an understandable report to the user, helping him/her to get into their dream university. In addition, this paper gives an outlook to further research in the context of an automated analysis of social media content to support the evaluation of universities.