using System;

using System.Collections.Generic;

using System.Linq;

​

public class SentimentAnalyzer

{

    public static string ClassifyText(string text, Dictionary<string, Dictionary<string, int>> trainingData)

    {

        string[] words = text.Split(' ');

​

        double positiveProbability = CalculateSentimentProbability("positive", words, trainingData);

        double negativeProbability = CalculateSentimentProbability("negative", words, trainingData);

​

        return positiveProbability >= negativeProbability ? "positive" : "negative";

    }

​

    private static double CalculateSentimentProbability(string sentiment, string[] words, Dictionary<string, Dictionary<string, int>> trainingData)

    {

        double probability = 1.0;

​

        if (!trainingData.ContainsKey(sentiment))

        {

            return 0; // Or throw an exception, depending on desired behavior

        }

​

        Dictionary<string, int> wordCounts = trainingData[sentiment];

        int totalWordsInSentiment = wordCounts.Values.Sum();

​

        foreach (string word in words)

        {

            if (wordCounts.ContainsKey(word))

            {

                probability *= (double)wordCounts[word] / totalWordsInSentiment;

            }

        }

​

        return probability;

    }

​

     public static void Main(string[] args)

    {

        var trainingData = new Dictionary<string, Dictionary<string, int>>

        {

            {

                "positive", new Dictionary<string, int>

                {

                    { "good", 10 },

                    { "great", 8 },

                    { "awesome", 5 },

                    { "bad", 2 }

                }

            },

            {

                "negative", new Dictionary<string, int>

                {

                    { "bad", 7 },

                    { "terrible", 5 },

                    { "awful", 3 },

                    { "good", 2 }

                }

            }

        };

​

        string text1 = "good great awesome";

        string sentiment1 = ClassifyText(text1, trainingData);

        Console.WriteLine($"'{text1}' is classified as: {sentiment1}");

​

        string text2 = "bad terrible awful";

        string sentiment2 = ClassifyText(text2, trainingData);

        Console.WriteLine($"'{text2}' is classified as: {sentiment2}");

​

        string text3 = "good bad";

        string sentiment3 = ClassifyText(text3, trainingData);

        Console.WriteLine($"'{text3}' is classified as: {sentiment3}");

​

        string text4 = "this is a test"; // test with words not in training data

        string sentiment4 = ClassifyText(text4, trainingData);

        Console.WriteLine($"'{text4}' is classified as: {sentiment4}");

        string text5 = "good bad awful great";

        string sentiment5 = ClassifyText(text5, trainingData);

        Console.WriteLine($"'{text5}' is classified as: {sentiment5}");

    }

}