A Unified Generative Artificial Intelligence Approach for Converting Social Media Content

Abstract

Social media content is relevant for many applications, including applications that assist in fighting the plague of terrorism through Artificial Intelligence (AI). However, social media content is diverse in its form - text, image, audio, and video. Depending on the nature of the applications, it may be desirable to convert all these forms into a unique format to ease processing. Once the data is converted into text, it is then possible to organize it into structured tabular data to feed Machine Learning (ML) algorithms for real-time terrorist attack detections. This paper explores using the emerging Generative Artificial Intelligence (Gen AI) tools for converting social media content (text, image, audio or video) into text format suitable for applying machine learning algorithms. The methodology of this research consisted of studying existing Gen AI tools, evaluating and selecting the best among those that offer API or code integration to implement a tool for converting all forms of social media content into text. The main limitation of this work is the small size of the datasets used in the tools’ evaluation. The design and implementation of the proposed solution have been completed, and the tool is ready for use and integration into a framework for collecting and analysing social media content to fight against terrorism.