ANALISIS SENTIMEN PADA TWITTER TERHADAP UIN RADEN FATAH MENGGUNAKAN SUPPORT VECTOR MACHINE
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Summary
Public opinion regarding UIN Raden Fatah Palembang was analysed using Support VectorMachine (SVM) method in determining the positive or negative sentiment of a tweet by doing initial processing for unstructured data from Twitter.
- Type
- article
- Published
- 2022-03-17
- Cited by
- 3
- References
- 14
- Access
- Open access
- OpenAlex
- https://openalex.org/W4220883883
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:247530679
Keywords
Support vector machine, Social media, Sentiment analysis, Computer science, Service (business)
References
- Improving Blog Polarity Classification via Topic Analysis and Adaptive Methods
- Modeling Public Mood and Emotion: Twitter Sentiment and Socio-Economic Phenomena
- Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer
- Personal Learning Environments, social media, and self-regulated learning: A natural formula for connecting formal and informal learning
- Sentiment Analysis and Opinion Mining
- Dataset Indonesia untuk Analisis Sentimen
- Teaching with Technology: Strategies for Engaging Learners
- Opinion Mining and Sentiment Analysis
Cited by
- ANALISIS SENTIMEN KEBIJAKAN PENYELENGGARA SISTEM ELEKTRONIK LINGKUP PRIVAT MENGGUNAKAN PENALIZED LOGISTIC REGRESSION DAN SUPPORT VECTOR MACHINE
- Sentiment Sentiment Analysis of Social Media X Users on the Decline of Marriage Rates in Indonesia
- Sentiment Analysis and Complaint Patterns on GoFood Merchants Using Naïve Bayes and Apriori
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