我正在尝试使用standford nlp来获取文本的情绪: 这是我的代码:
import java.util.Properties;
import edu.stanford.nlp.ling.CoreAnnotations;
import edu.stanford.nlp.pipeline.Annotation;
import edu.stanford.nlp.pipeline.StanfordCoreNLP;
import edu.stanford.nlp.rnn.RNNCoreAnnotations;
import edu.stanford.nlp.sentiment.SentimentCoreAnnotations;
import edu.stanford.nlp.trees.Tree;
import edu.stanford.nlp.util.CoreMap;
public class SentimentAnalyzer {
public static void main(String[] args) {
findSentiment("");
}
public static void findSentiment(String line) {
line = "I started taking the little pill about 6 years ago.";
Properties props = new Properties();
props.setProperty("annotators", "tokenize, ssplit, parse, sentiment");
StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
int mainSentiment = 0;
if (line != null && line.length() > 0) {
int longest = 0;
Annotation annotation = pipeline.process(line);
for (CoreMap sentence : annotation
.get(CoreAnnotations.SentencesAnnotation.class)) {
Tree tree = sentence
.get(SentimentCoreAnnotations.AnnotatedTree.class);
int sentiment = RNNCoreAnnotations.getPredictedClass(tree);
String partText = sentence.toString();
if (partText.length() > longest) {
mainSentiment = sentiment;
longest = partText.length();
}
}
}
if (mainSentiment == 2 || mainSentiment > 4 || mainSentiment < 0) {
System.out.println("Neutral " + line);
}
else{
}
/*
* TweetWithSentiment tweetWithSentiment = new TweetWithSentiment(line,
* toCss(mainSentiment)); return tweetWithSentiment;
*/
}
}
我也使用此链接中的说明: https://blog.openshift.com/day-20-stanford-corenlp-performing-sentiment-analysis-of-twitter-using-java/
但是我收到以下错误:
Exception in thread "main" java.lang.NullPointerException
at edu.stanford.nlp.rnn.RNNCoreAnnotations.getPredictedClass(RNNCoreAnnotations.java:58)
at SentimentAnalyzer.findSentiment(SentimentAnalyzer.java:27)
at SentimentAnalyzer.main(SentimentAnalyzer.java:14)
指向这一行:
Tree tree = sentence.get(SentimentCoreAnnotations.AnnotatedTree.class);
有没有人有任何想法?
答案 0 :(得分:6)
请改用:
Tree tree = sentence.get(SentimentCoreAnnotations.SentimentAnnotatedTree.class);
修改强> 要获得积极,消极和中立的评论,请使用以下代码段:
switch (mainSentiment) {
case 0:
return "Very Negative";
case 1:
return "Negative";
case 2:
return "Neutral";
case 3:
return "Positive";
case 4:
return "Very Positive";
default:
return "";
}