Tight competition among companies has been making many companies to increase their efforts to collect information for the sake of their service analysis. Recorded data in Twitter can be used as a potential data which is becoming one of the most popular social media in the world. Naive Bayes is developed to observe positive and negative opinions of the customers on the services given by the company in the form of heat map. Data pre-processing was performed in order to determine attributes to choose data accompanying with their associated coordinates and to decide which words are considered as positive or negative opinion. Heat map was used to visualize density level gradation of opinions. The use of heat map is capable to observe customer's opinions density level based on their colour gradation visualization that are presented in certain radius from one coordinate observing point specified by the user.

Original languageEnglish
Pages (from-to)1182-1188
Number of pages7
JournalJournal of Engineering and Applied Sciences
Issue number4
Publication statusPublished - 2019


  • Classification
  • Emotions
  • Heat map
  • Naive Bayes
  • Opinion
  • Twitter


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