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03_​Sentiment_​Analysis_​Lexicon_​Based_​Approach

03_Lexicon Based Approach for Sentiment Analysis
Lexicon Based Approach for Sentiment Analysis This workflow shows how to perform a lexycon based approach for sentiment analysis of IMDB reviews dataset. The dataset contains movie reviews, previously labelled as positive/negative.The lexicon based approach assigns a sentiment to each word in a text based on dictionaries of positive and negative words. A sentiment score is then calculated for each document as: (number of positive words - number of negative words) / total number of words. Dataset ReferenceAndrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. (2011). Learning Word Vectors for Sentiment Analysis. The 49th Annual Meeting of the Associationfor Computational Linguistics (ACL 2011). MPQADictionaries Read articles from IMDB datasetColor by sentimentlabelCount number of wordsfor each documentCount number ofpositive and negativewords in documentand extract termscleaningstemmingtag filteringAssign PositiveTagsAssign Negative TagsAccuracyPositive listNegative list Reading Data Color Manager GroupBy Aggregate Pre-processing Dictionary Tagger Dictionary Tagger Calculate Score BoW - TF Scorer CSV Reader CSV Reader Lexicon Based Approach for Sentiment Analysis This workflow shows how to perform a lexycon based approach for sentiment analysis of IMDB reviews dataset. The dataset contains movie reviews, previously labelled as positive/negative.The lexicon based approach assigns a sentiment to each word in a text based on dictionaries of positive and negative words. A sentiment score is then calculated for each document as: (number of positive words - number of negative words) / total number of words. Dataset ReferenceAndrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. (2011). Learning Word Vectors for Sentiment Analysis. The 49th Annual Meeting of the Associationfor Computational Linguistics (ACL 2011). MPQADictionaries Read articles from IMDB datasetColor by sentimentlabelCount number of wordsfor each documentCount number ofpositive and negativewords in documentand extract termscleaningstemmingtag filteringAssign PositiveTagsAssign Negative TagsAccuracyPositive listNegative listReading Data Color Manager GroupBy Aggregate Pre-processing Dictionary Tagger Dictionary Tagger Calculate Score BoW - TF Scorer CSV Reader CSV Reader

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Created by: Kilian
Created at: 2014-10-20
On NodePit since: 2021-03-10
Last update: 2024-04-28
Created with KNIME version: v4.5.0
Tags: BooksFrom Words To WisdomText Mining

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