please dont use Ai

Fuzzy Logic-Based Fake News Detection Example Suppose we have a news article with the following features that you use to determine whether the article is likely to be fake news: This Task involves working on several problems, and you will use fuzzy set theory to solve them. Word Count: The total number of words in the article. Emotional Tone: A score indicating the article's emotional tone (positive, negative, or neutral). Source Reliability: A rating (on a scale of 0 to 1) representing how reliable the news source is. To describe the qualitative characteristics of the above features and represent its inherently vague or imprecise, we use these linguistic variables: Word Count: Low, Medium, High Emotional Tone: Negative, Neutral, Positive Source Reliability: Low, Medium, High These membership functions represent each feature. Word Count Emotional Tone Universe of discourse (U): Set of possible | Universe of discourse (U): Set of emotional word counts (e.g., U = [0, 1000]) tone scores (e.g., U = [-1, 1]] *= 200 1, 15-0.5 x - 200 -0.5 - X 200 - 1000 200