Social media allows institutions to not only publicize their work and get feedback from
the community about it, but also to keep in touch with their alumni network and foster
conversations between the academic community. While sentiment analysis allows a better
understanding of what is being said about a brand and how to improve the use of this
communication platform. The main goal of the current work is to build a Business
Intelligence System for a Higher Education Institution (HEI) based on content extracted
from social media. So, Posts, likes, dislikes, shares, comments and number of visits were
extracted from Facebook, Google Maps Reviews, Instagram, LinkedIn, Student Forums,
Twitter and YouTube. With this data and the ETL process a Data Warehouse (DW) in
SQL Server and 17 Dashboards in Power BI were developed. Posts that had the most likes
were about reporting a death of someone from the school, the school mascot, the
pandemic or welcoming new students. Overall, the weekends were the days with more
interactions. Students are concerned about accommodation, transport, and the school
academic offer. This analysis allows a better understanding of what is being said about
this HEI and how to improve the communication strateg
