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03_​Sentiment_​Classification

Sentiment Analysis (Classification) of Documents

This workflow shows how to import text from a csv file, convert it to documents, preprocess the documents and transform them into numerical document vectors. Finally two predictive models are trained on the vectors to predict the sentiment class of the documents.

URL: Sentiment Classification of Documents http://www.knime.org/blog/sentiment-analysis
URL: Read more about "Lexicon-based sentiment analysis: A tutorial" https://www.knime.com/blog/lexicon-based-sentiment-analysis

Sentiment Classification of Documents

This workflow reads IMDb movie reviews (.csv), converts it to documents, preprocess the documents and transform them into numerical document vectors. Finally two predictive models are trained on the vectors to predict the sentiment class of the documents.

Data Import and Preprocessing

Predictive Modeling and Scoring

Column Appender
Column Filter
Preprocessing of documents
Preprocessing
Create bit vectorsfor documents
Document Vector
Decision Tree Learner
ROC Curve
Read IMDb reviews from CSV file
CSV Reader
XGBoost Tree Ensemble Learner
Color by sentiment label
Color Manager
Transformation of strings to documents
Document Creation
Extract sentiment label
Category to Class
Training / test set
Table Partitioner
XGBoost Predictor
Decision Tree Predictor
Scorer
Scorer

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: Kilian
Created at: 2014-11-08
On NodePit since: 2026-05-12
Last update: 2026-05-12
Created with KNIME version: v5.10.0
Tags: sentiment analysisNLPNatural Language Processingtext classificationPracticing Data Science

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