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

2. 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

3. 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