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
