#AIImpactOnForex Handling negation and sarcasm in Forex text data presents a significant challenge for sentiment analysis. Simple lexicon-based approaches often fail to correctly interpret sentences where the sentiment of words is reversed by negating terms like "not" or "no." Similarly, sarcasm, where the intended meaning is the opposite of the literal words used, can easily mislead sentiment analysis models. More advanced NLP techniques, including dependency parsing to understand grammatical relationships and contextual understanding through machine learning models, are employed to address these complexities. Identifying negations and sarcastic remarks requires analyzing the surrounding words and the overall context of the sentence to accurately determine the true sentiment being expressed in Forex-related communications.