Find Most Frequent Word in C, C++, Java & Python – Code with Explanation & Examples in Short and Simple

   

C Program

#include <stdio.h>
#include <string.h>

int main() {
    char str[200] = "apple banana apple orange banana apple";
    char words[50][50];
    int count[50] = {0}, i, j, k = 0, n = 0;

    char *token = strtok(str, " ");
    while (token != NULL) {
        int found = 0;
        for (i = 0; i < n; i++) {
            if (strcmp(words[i], token) == 0) {
                count[i]++;
                found = 1;
                break;
            }
        }
        if (!found) {
            strcpy(words[n], token);
            count[n] = 1;
            n++;
        }
        token = strtok(NULL, " ");
    }

    int max = 0, index = 0;
    for (i = 0; i < n; i++) {
        if (count[i] > max) {
            max = count[i];
            index = i;
        }
    }

    printf("Most frequent word: %s (%d times)\n", words[index], max);
    return 0;
}

C Output

Most frequent word: apple (3 times)

C++ Program

#include <iostream>
#include <sstream>
#include <map>
using namespace std;

int main() {
    string str = "dog cat dog bird cat dog";
    map<string, int> freq;
    string word;

    stringstream ss(str);
    while (ss >> word) {
        freq[word]++;
    }

    string mostWord;
    int maxCount = 0;
    for (auto &p : freq) {
        if (p.second > maxCount) {
            maxCount = p.second;
            mostWord = p.first;
        }
    }

    cout << "Most frequent word: " << mostWord << " (" << maxCount << " times)\n";
    return 0;
}

C++ Output

Most frequent word: dog (3 times)

JAVA Program

import java.util.*;

public class Main {
    public static void main(String[] args) {
        String str = "java python java c java python";
        String[] words = str.split(" ");
        HashMap<String, Integer> map = new HashMap<>();

        for (String w : words) {
            map.put(w, map.getOrDefault(w, 0) + 1);
        }

        String mostWord = "";
        int max = 0;
        for (Map.Entry<String, Integer> e : map.entrySet()) {
            if (e.getValue() > max) {
                max = e.getValue();
                mostWord = e.getKey();
            }
        }

        System.out.println("Most frequent word: " + mostWord + " (" + max + " times)");
    }
}

JAVA Output

Most frequent word: java (3 times)

Python Program

from collections import Counter

s = "red blue red green red blue"
words = s.split()
counter = Counter(words)
word, freq = counter.most_common(1)[0]
print(f"Most frequent word: {word} ({freq} times)")

Python Output

Most frequent word: red (3 times)

In-Depth Explanation

Example

Suppose the string is "apple banana apple orange banana apple". We divide it into words: [apple, banana, apple, orange, banana, apple]. Occurrences counted, we have apple = 3, banana = 2, and orange = 1. As apple has the highest count, it is the most frequent word.

Real-Life Analogy

Consider this problem similar to running a popularity contest with words. Think of a class where students vote for their favorite fruit by marking its name. After gathering all slips, you tally how often each fruit appears. The fruit appearing most often is the "most frequent" — similar to the word in our problem. 

Why It Matters

This principle is extensively applied in text analysis and Natural Language Processing (NLP). For instance, identifying the most common word or hashtag in social media websites aids in determining trending topics. In online businesses, product review analysis to determine the most common words (such as "quality", "price", "delivery") provides companies with customer satisfaction information. Even search engines such as Google employ word frequency analysis in their ranking algorithm.

Learning Insights

From the programming point of view, it is an exercise in string parsing, frequency counting, and use of dictionary/map. It acquaints you with the concept of employing data structures such as hash maps (dictionary in Python, HashMap in Java, map in C++) to store and increment counts efficiently. It is a bridge to more advanced subjects such as inverted indexes, word clouds, and TF-IDF in information retrieval.

Interview Relevance

This is a very popular interview question since it exercises several skills: working with strings, making good use of data structures, and coding nicely. Interviewers might even throw in a variation where they ask you to return the k most frequent words or to deal with extremely large sets of data where there is little memory available.

Real-World Applications

Search Engines: In order to understand which keywords occur most in queries.

Chatbots & NLP: To identify intent out of repeated sentences.

E-commerce Reviews: Determining the most common issues or compliments.

Data Science: Constructing word frequency distribution for predictive models.

SEO Optimized Closing

Knowing how to discover the most common word in a string is a fundamental principle of programming, data science, and natural language processing. It educates new users on the significance of string manipulation, frequency, and effective utilization of maps or dictionaries. By solving this problem, students are well-prepared to answer interview questions and practical applications like sentiment analysis of customer reviews, trending hashtag detection, and search query processing. Solving this problem in C, C++, Java, and Python builds solid problem-solving foundations and thus is a must-solve problem for everyone learning to code and facing placements.