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Ho bisogno di fare analisi del sentimento su alcuni file CSV contenenti tweet. Sto usando SentiWordNet per fare l'analisi dei sentimenti.Come utilizzare SentiWordNet
Ho ottenuto il seguente codice di esempio java che hanno fornito sul loro sito. Non sono sicuro di come usarlo. Il percorso del file csv che voglio analizzare è C:\Users\MyName\Desktop\tweets.csv. Il percorso di SentiWordNet_3.0.0.txt è C:\Users\MyName\Desktop\SentiWordNet_3.0.0\home\swn\www\admin\dump\SentiWordNet_3.0.0_20130122.txt. Sono nuovo di java, pls help, grazie! Il collegamento al codice java di esempio riportato di seguito è this.
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 SWN3 {
private String pathToSWN = "data"+File.separator+"SentiWordNet_3.0.0.txt";
private HashMap<String, String> _dict;
public SWN3(){
_dict = new HashMap<String, String>();
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, sent);
}
}
catch(Exception e){e.printStackTrace();}
}
public String extract(String word, String pos)
{
return _dict.get(word+"#"+pos);
}
}
Nuovo codice:
public class SWN3 {
private String pathToSWN = "C:\\Users\\MyName\\Desktop\\SentiWordNet_3.0.0\\home\\swn\\www\\admin\\dump\\SentiWordNet_3.0.0.txt";
private HashMap<String, String> _dict;
public SWN3(){
_dict = new HashMap<String, String>();
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, sent);
}
}
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 String classifytweet(){
String[] words = twit.split("\\s+");
double totalScore = 0, averageScore;
for(String word : words) {
word = word.replaceAll("([^a-zA-Z\\s])", "");
if (_sw.extract(word) == null)
continue;
totalScore += _sw.extract(word);
}
Double AverageScore = totalScore;
if(averageScore>=0.75)
return "very positive";
else if(averageScore > 0.25 && averageScore<0.5)
return "positive";
else if(averageScore>=0.5)
return "positive";
else if(averageScore < 0 && averageScore>=-0.25)
return "negative";
else if(averageScore < -0.25 && averageScore>=-0.5)
return "negative";
else if(averageScore<=-0.75)
return "very negative";
return "neutral";
}
public static void main(String[] args) {
// TODO Auto-generated method stub
}
Ciao, grazie per la risposta, non sono ancora chiaro su alcune parti. Cosa significa questo? if (_dict.get (word + "# r")! = null) # n, # a, # r, # v? Grazie! – Belgarion
Se osservate la prima colonna del file, noterete queste lettere (che sta per * noun *, * verb * ..) quindi dovreste coprire tutti i casi. – Maroun
Ah capisco. Ho ancora bisogno di un po 'più di aiuto, dove posso inserire il mio link nel mio file tweet.csv? C: \ Users \ MyName \ Desktop \ tweets.csv Ho incollato il mio codice aggiornato sopra, sentitevi liberi di modificarlo, grazie! – Belgarion