Grouping and Categorizing Data from Social Networking Applications for Forensic Analysis

Social media has become a new trend in the lifestyle of modern society. It provides an indispensable data source for daily life, with widespread use worldwide. This research aims to simplify the complexity of social networking application data and provide key information needed in forensic investigations. Specifically, the objectives are to identify the types of data that can be collected from Twitter and Instagram and develop a methodology to efficiently and effectively group and categorize the data to answer the key forensic questions of Who, Where, What, When, Why, and How. The proposed methodology includes automated web crawling using Apify, grouping and categorizing data based on key parameters, and storing and managing PostgreSQL data. This research targets law enforcement and forensic analysts, providing them with a robust tool for digital forensic investigations. The results of this study show that the methodology successfully simplifies social media data, making it more structured and easier to analyze for forensic purposes.