Sentimental Analysis using WordNet Dictionary

Sentimental Analysis using WordNet Dictionary

 This is the sample program to calculate the each and every word of semantic orientation by using sentiwordnet dictionary.

package com.orienit.hadoop.training;

import java.io.BufferedReader;
import java.io.File;
import java.io.FileReader;
import java.util.HashMap;
import java.util.Iterator;
import java.util.Set;
import java.util.Vector;

    public class SentimentalWordNet {
        private String pathToSWN = "/home/hadoop/work/SentiWordNet_3.0.0.txt";
        private HashMap<String, Double> _dict;

        public SentimentalWordNet(){

            _dict = new HashMap<String, Double>();
            HashMap<String, Vector<Double>> _temp = new HashMap<String, Vector<Double>>();
            try{
                BufferedReader csv =  new BufferedReader(new FileReader(pathToSWN));
                String line = "";
                while((line = csv.readLine()) != null)
                {
                    String[] data = line.split("\t");
                    Double score = Double.parseDouble(data[2])-Double.parseDouble(data[3]);
                    String[] words = data[4].split(" ");
                    for(String w:words)
                    {
                        String[] w_n = w.split("#");
                        w_n[0] += "#"+data[0];
                        int index = Integer.parseInt(w_n[1])-1;
                        if(_temp.containsKey(w_n[0]))
                        {
                            Vector<Double> v = _temp.get(w_n[0]);
                            if(index>v.size())
                                for(int i = v.size();i<index; i++)
                                    v.add(0.0);
                            v.add(index, score);
                            _temp.put(w_n[0], v);
                        }
                        else
                        {
                            Vector<Double> v = new Vector<Double>();
                            for(int i = 0;i<index; i++)
                                v.add(0.0);
                            v.add(index, score);
                            _temp.put(w_n[0], v);
                        }
                    }
                }
                Set<String> temp = _temp.keySet();
                for (Iterator<String> iterator = temp.iterator(); iterator.hasNext();) {
                    String word = (String) iterator.next();
                    Vector<Double> v = _temp.get(word);
                    double score = 0.0;
                    double sum = 0.0;
                    for(int i = 0; i < v.size(); i++)
                        score += ((double)1/(double)(i+1))*v.get(i);
                    for(int i = 1; i<=v.size(); i++)
                        sum += (double)1/(double)i;
                    score /= sum;
                    String sent = "";
                    if(score>=0.75)
                        sent = "strong_positive";
                    else
                    if(score > 0.25 && score<=0.5)
                        sent = "positive";
                    else
                    if(score > 0 && score>=0.25)
                        sent = "weak_positive";
                    else
                    if(score < 0 && score>=-0.25)
                        sent = "weak_negative";
                    else
                    if(score < -0.25 && score>=-0.5)
                        sent = "negative";
                    else
                    if(score<=-0.75)
                        sent = "strong_negative";
                    _dict.put(word, score);
                }
            }
            catch(Exception e){
             //e.printStackTrace();
             }        

        }

public Double extract(String word)
{
    Double total = new Double(0);
    if(_dict.get(word+"#n") != null)
         total = _dict.get(word+"#n") + total;
    if(_dict.get(word+"#a") != null)
        total = _dict.get(word+"#a") + total;
    if(_dict.get(word+"#r") != null)
        total = _dict.get(word+"#r") + total;
    if(_dict.get(word+"#v") != null)
        total = _dict.get(word+"#v") + total;
    return total;
}

public static void main(String[] args) {
    SentimentalWordNet test = new SentimentalWordNet();
    String sentence="hey i had a wonderful an experience in barista";
    String[] words = sentence.split("\\s+");
    double totalScore = 0;
    for(String word : words) {
        word = word.replaceAll("([^a-zA-Z\\s])", "");
        if (test.extract(word) == null)
            continue;
        totalScore += test.extract(word);
    }
    if(totalScore == 0)
    {
      System.out.println("Neutral Statement :" + totalScore);
    } else if(totalScore > 0) {
      System.out.println("Postive Statement :" + totalScore);
    } else {
      System.out.println("Negative Statement :" + totalScore);
    }
}

}

OUTPUT:-

Postive Statement :0.34798245187641463

Note: Find the attached link for sentimentalwordnetdictionary. Remove the all comments and hash tag from the beginning and end of the file.

http://sentiwordnet.isti.cnr.it/download.php