Stanford NLP für Sentiment-Analyse von Tweets Stufen

Question

Die ursprünglichen Tweets in eine Datei in der folgenden Struktur gespeichert wurden:

Tweet Sprache || tweet

Das folgende ist meine Vorverarbeitungsstufe, um URLs, RT, Benutzernamen und alle nicht-alphanumerischen Zeichen zu entfernen.

def cleanTweets() {

File dirtyTweets = new File("result.txt") 
    File cleanTweets = new File("cleanTweets.txt") 

    try { 
     Scanner console = new Scanner(dirtyTweets) 

     PrintWriter printWriter = new PrintWriter(new BufferedWriter(new FileWriter(cleanTweets))) 
     LinkedHashSet<String> ln = new LinkedHashSet<String>(); 

     while (console.hasNextLine()) { 

      String line = console.nextLine(); 

      String[] splitter = line.split("\\|\\|\\|") 
      //Only looks at the english tweets 
      if (splitter[0] == "en") { 

       line = line.replaceFirst("en", "") 

       String urlIdentifier = "((http|ftp|https):\\/\\/)?[\\w\\-_]+(\\.[\\w\\-_]+)+([\\w\\-\\.,@?^=%&amp;:/~\\+#]*[\\w\\-\\@?^=%&amp;/~\\+#])?" 

       //Removes URL's, RT, Twitter usernames and any non alpha numeric character 
       String[] removeNoise = ["RT", urlIdentifier, "(?:\\s|\\A)[@]+([A-Za-z0-9-_]+)", "[^a-zA-Z0-9 ]"] 

       removeNoise.each { noise -> 
        line = line.replaceAll(noise, "").toLowerCase() 
       } 
       ln.add(line) 

      } 
     } 

     ln.each { line -> 
      printWriter.write(line) 
      printWriter.println() 
     } 
     //write to file here 
    } catch (IOException e) { 
    } 
} 

Dieses wird dann in eine neue Datei gespeichert. Was wäre die nächste Stufe für die Stimmungsanalyse dieser Tweets?

Answer 1

Hier ist ein Beispielcode das Gefühl Kommentator für die Verwendung:

package edu.stanford.nlp.examples; 

import edu.stanford.nlp.ling.*; 
import edu.stanford.nlp.pipeline.*; 
import edu.stanford.nlp.sentiment.*; 
import edu.stanford.nlp.util.*; 
import java.util.Properties; 

public class SentimentExample { 

    public static void main(String[] args) { 
    Annotation document = new Annotation("...insert tweet text here..."); 
    Properties props = new Properties(); 
    props.setProperty("annotators", "tokenize,ssplit,pos,lemma,ner,parse,sentiment"); 
    // you might want to enforce treating the entire tweet as one sentence 
    //...if so uncomment the line below setting ssplit.eolonly to true 
    // also make sure you remove newlines, this will prevent the 
    // sentence splitter from dividing the tweet into different sentences 
    //props.setProperty("ssplit.eolonly","true"); 
    props.setProperty("parse.binaryTrees","true"); 
    StanfordCoreNLP pipeline = new StanfordCoreNLP(props); 
    pipeline.annotate(document); 
    for (CoreMap sentence : document.get(CoreAnnotations.SentencesAnnotation.class)) { 
     System.out.println("---"); 
     System.out.println(sentence.get(CoreAnnotations.TextAnnotation.class)); 
     System.out.println(sentence.get(SentimentCoreAnnotations.SentimentClass.class)); 
    } 
    } 
}