Application of Natural Language Processing and Fuzzy Logic to Disinformation Detection

Natural language processing (NLP) is a field of computer science that is concerned with processing, collection and analysis of data encoded in natural language, such as speech, written text, online posts, etc. This paper explores the integration of Natural Language Processing (NLP) methods, specifically TF-IDF and n-gram analysis, with fuzzy logic rules employing Gaussian membership functions to detect disinformation in text data. The approach emphasizes reducing false positives by assessing the probability of disinformation rather than binary decisions, enhancing the accuracy and reliability of text analysis under informational uncertainty.