TOPIC ANALYSIS ON SOCIAL NETWORKS USING NATURAL LANGUAGE PROCESSING (NLP)

Abstract

This article investigates the role of Natural Language Processing (NLP) in topic analysis on social networks. It discusses the fundamentals of NLP, its main challenges, and techniques, as well as illustrating how they contribute to the understanding and processing of human language by Artificial Intelligence systems. Through a qualitative study, data from Twitter/X and Reddit were collected and processed using each platform's API and data scraping techniques. The collected data were cleaned and normalized, then analyzed using NLP techniques such as lemmatization, the bag of words method, and TF-IDF. The main objective of the study is to develop a solid understanding of NLP and its techniques, and to apply them to relevant data collected from social networks to identify trends and relevant topics. This investigation highlights the importance of NLP in today's digital world, where data analysis on social platforms has become crucial to understand trends and behaviors. The article also emphasizes the relevance of advanced NLP techniques in extracting meaningful insights from large textual datasets and in overcoming the challenges inherent to human language.