A Data-Driven Analysis of Reach and Interaction on the “ISAP -Computer Engineering Department” Facebook Page

Abstract

This research paper looks at how people interact with the "ISAP - Computer Engineering Department" Facebook page in a systematic way. The study looks at key metrics like reach, engagements, shares, likes, and comments using historical data from May 8, 2023, to August 7, 2023. The methodology includes data collection, preprocessing, exploratory data analysis, distribution analysis, correlation analysis, and strategic recommendations. Correlations between metrics were looked at to figure out the complex relationships that drive engagement, and content analysis was done to figure out the things that lead to higher reach. The results give a more nuanced picture of how content connects with the audience, which paves the way for targeted strategies to increase both reach and engagement. Ethical concerns were taken into account, which made sure that research was done in a responsible way. The insights from this study can help content creators, social media managers, and teachers improve the performance of their Facebook pages and build a more active online community