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SentimentAnalysisOntologyBased

Ontology-based Sentiment Analysis on the Twitter - Indonesian President Election Campaign 2019 Study Case

We developed an ontology based on the dataset -> "Ekonomi" with three attributes i.e., "Finansial", "Lapangan Kerja", "Kesejahteraan".

Then we calculate the sentimen of the tweets and summarize the sentiment results based on the ontology attributes.

Raw Dataset

  • Extract file on the data/allchunk_dataset_raw.zip
  • We already processed the raw dataset to the labelled tweets on the Sampel600.xlsx

Methodology

  1. Data Acquisition
  • Tweet selection -> tweetmanipulation.py
  1. Development of Ontology
  • Make initial ontology -> ontology.py
  • Preprocessing -> utils.py & ontology.py
  • Update the ontology to Final Ontology using WordCloud -> tweetmanipulation.py
  • Classify the tweets based on the Final Ontology -> ontology.py
  1. Sentiment Analysis
  • Sentiment analysis by Lexicon-based -> sentimenlexicon.py
  • Sentiment analysis by SVM -> sentimenklasifikasisvm.py
  • Measuring performance -> performance.py
  • Mapping the sentimen based on the ontology -> tweetontology.py