Implementation of K-Means Algorithm to Classify Instagram Reels and Carousel Content Performance Based

Abstract

With the increasing popularity of digital marketing, Instagram became one of the top platforms where the audience can be reached. It is important to gain an insight into the performance of different types of contents to ensure that the marketing efforts bear fruit. This research will apply the K-Means algorithm to classify Instagram Reels and Carousel contents based on performance by taking into account such factors as likes, comments, shares, and saves. For the purposes of the study, the data were collected from a variety of accounts both personal and of a business nature. The number of clusters was defined by the Elbow Method, after which they were categorized depending on their performance such as high, medium, and low. The results indicate that the classification based on performance provided by the K-Means algorithm can provide insights into marketing practices on Instagram. Consequently, the present research will contribute to the development of digital marketing studies, particularly in the area of content analysis, within the field of data mining.