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Sentiment_​Dictionary_​Based

Rule-based Prediction with Dictionary TaggerThis workflow reads the IMDb dataset as well as a list of positive and negative words. After tagging the positive and negative words in the reviews, the workflow uses the Tag Filter node to delete all words which have neither a positive nor a negative sentiment. In the next step, it counts the number of positive and negative words per document (Pivoting node) and calculates the Sentiment Score(#positive-#negative)/(#all words) before it makes the predictions based on the sentiment score. In the last step, it extracts the correct labels to evaluate the model. Preprocessing Enrichment Transformation and Frequencies Reading and Parsing Classification Evaluation Filter all columnsexcept the documentcolumnConvert strings toto documentsExtract sentimentlabelRead IMDb reviewsfrom CSV filePositive listNegative listBy documentsvia sentimentsTF absoluteFiltered wordsSentiment score#Positive-#NegativePredict sentimentbased on scoreAssign positivetagsAssign negativetags Column Filter Strings To Document Category To Class File Reader File Reader File Reader Tags To String Pivoting TF Tag Filter Bag Of WordsCreator Math Formula Rule Engine Scorer Missing Value Dictionary Tagger Dictionary Tagger Rule-based Prediction with Dictionary TaggerThis workflow reads the IMDb dataset as well as a list of positive and negative words. After tagging the positive and negative words in the reviews, the workflow uses the Tag Filter node to delete all words which have neither a positive nor a negative sentiment. In the next step, it counts the number of positive and negative words per document (Pivoting node) and calculates the Sentiment Score(#positive-#negative)/(#all words) before it makes the predictions based on the sentiment score. In the last step, it extracts the correct labels to evaluate the model. Preprocessing Enrichment Transformation and Frequencies Reading and Parsing Classification Evaluation Filter all columnsexcept the documentcolumnConvert strings toto documentsExtract sentimentlabelRead IMDb reviewsfrom CSV filePositive listNegative listBy documentsvia sentimentsTF absoluteFiltered wordsSentiment score#Positive-#NegativePredict sentimentbased on scoreAssign positivetagsAssign negativetags Column Filter Strings To Document Category To Class File Reader File Reader File Reader Tags To String Pivoting TF Tag Filter Bag Of WordsCreator Math Formula Rule Engine Scorer Missing Value Dictionary Tagger Dictionary Tagger

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Created by: Kilian
Created at: 2014-11-08
On NodePit since: 2020-06-24
Last update: 2024-04-20
Created with KNIME version: v4.1.3

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