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rightAnswers += d; }
} System.out.println;
} float accuration;
int rows = 0; for int i = 0; i row.length; i++ {
rows += row[i]; }
System.out.println; accuration = float rightAnswers rows 100;
System.out.printlnAccuration = + accuration + ; }
}
13. PreprocessingWeighting.java
package sentimentanalysis; import java.io.IOException;
import java.util.ArrayList; import java.util.LinkedHashMap;
import sentimentanalysis.WordFreq.Word; public class PreprocessingWeighting {
public static void mainString[] args throws IOException, Exception { TODO code application logic here
int n = 200;
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System.out.printTokenizing : ; Tokenizing love = new Tokenizingdata ver.4cinta.txt;
Tokenizing anger = new Tokenizingdata ver.4marah.txt; Tokenizing sad = new Tokenizingdata ver.4sedih.txt;
Tokenizing happy = new Tokenizingdata ver.4senang.txt; Tokenizing fear = new Tokenizingdata ver.4takut.txt;
LinkedHashMapInteger, ArrayListString loveMap = love.getAllToken1; LinkedHashMapInteger, ArrayListString angerMap = anger.getAllToken1 + n;
LinkedHashMapInteger, ArrayListString sadMap = sad.getAllToken1 + 2 n; LinkedHashMapInteger, ArrayListString happyMap = happy.getAllToken1 + 3 n;
LinkedHashMapInteger, ArrayListString fearMap = fear.getAllToken1 + 4 n; LinkedHashMapInteger, ArrayListString tweetsMap = new LinkedHashMap;
tweetsMap.putAllloveMap; tweetsMap.putAllangerMap;
tweetsMap.putAllsadMap; tweetsMap.putAllhappyMap;
tweetsMap.putAllfearMap; LinkedHashMapInteger,
ArrayListString oriTweetsMap
= new
LinkedHashMaptweetsMap; System.out.printlndone;
for int key : tweetsMap.keySet { System.out.println\t + key + + tweetsMap.getkey;
} System.out.println\t + Size = + tweetsMap.size;
System.out.println; System.out.printRemoving Stopwords : ;
RemoveStopword removeStopword = new RemoveStopwordstopwords.txt; removeStopword.setWordsHashMaptweetsMap;
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tweetsMap = removeStopword.getWordsHashMap; System.out.printlndone;
for int key : tweetsMap.keySet { System.out.println\t + key + + tweetsMap.getkey;
} System.out.println\t + Size = + tweetsMap.size;
System.out.println; System.out.printStemming : ;
Stemming stemming = new Stemmingdictionary.txt, synonym.txt; tweetsMap = stemming.stemtweetsMap;
System.out.printlndone; for int key : tweetsMap.keySet {
System.out.println\t + key + + tweetsMap.getkey; }
System.out.println\t + Size = + tweetsMap.size; System.out.println;
System.out.printNegation Handling : ; NegationHandling negation = new NegationHandling;
tweetsMap = negation.negationHandlingtweetsMap; System.out.printlndone;
for int key : tweetsMap.keySet { System.out.println\t + key + + tweetsMap.getkey;
} System.out.println\t + Size = + tweetsMap.size;
System.out.println; System.out.printCounting Terms Freq : ;
ArrayListString words = new ArrayList; for int key : tweetsMap.keySet {
words.addAlltweetsMap.getkey;
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} Word[] wordFreq = new WordFreq.getFreqWordswords;
LinkedHashMapString, Integer wordsCount = new LinkedHashMap; for Word w : wordFreq {
wordsCount.putw.getWord, w.getCount; }
System.out.printlndone; for String key : wordsCount.keySet {
System.out.println\t + key + + wordsCount.getkey; }
System.out.println; ArrayListString terms = new ArrayList;
terms.addAllwordsCount.keySet; System.out.printForming Document Vector : ;
TfIdf tfIdf = new TfIdf; LinkedHashMapInteger, double[] features = tfIdf.tfIdfCalculatortweetsMap, terms;
System.out.printlndone; for int key : features.keySet {
System.out.println\t + key + + Arrays.toStringfeatures.getkey; }
System.out.println; CSV csv = new CSV;
csv.writeFreqToCSVwordsCount, freq.csv; csv.writeFeaturesToCSVfeatures, features.csv;
csv.writeTweetsToCSVoriTweetsMap, tweets.csv; }
}
14. Clustering.java
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package sentimentanalysis; import java.io.IOException;
import java.util.ArrayList; import java.util.Arrays;
import java.util.LinkedHashMap; import java.util.TreeSet;
public class Clustering { public static void mainString[] args throws IOException {
int k = 5; int minFreq = 3;
boolean zscore = false; boolean minmax = true;
int n = 5; CSV csv = new CSV;
LinkedHashMapInteger, double[] features = csv.readFeaturesFromCSVfeatures.csv; LinkedHashMapInteger,
ArrayListString tweets
= csv.readTweetsFromCSVtweets.csv;
LinkedHashMapString, Integer freq = csv.readFreqFromCSVfreq.csv; System.out.printlnAll Terms = + features.get1.length;
double m = features.get1[0]; for int key : features.keySet {
for double d : features.getkey { if d m {
m = d; }
