• social network
• facebook
• instagram
• customer engagement

In recent years, social media have become an important asset for companies to build relationships with their customers. However, creating effective content for social media marketing campaigns poses a challenge due to the unknown factors that contribute to a post's success. The information provided by social media users holds unprecedented potential for understanding the factors that drive user engagement. This study collects data from the social networks of a manufacturing company, specifically from Facebook and Instagram. The objective is to simplify the complex and multidimensional input space into a discrete output space, aiming at identifying the factors that lead to a post's success and guiding businesses to improve their marketing efforts. In this thesis, the popularity is explored through an approach based on textual and synthetic features. It involves extracting textual features from the post content as potentially influential factors and conducting subsequent analysis to examine the relationship between content features and engagement. The findings can serve as guidance for marketers in creating engaging content that effectively communicates with their customer base.