SENITMENT ANALYSIS ON WHO SOUTHEAST ASIA REGION ORGANIZATION (WHO SERO) USER COMMENT REVIEW AND OPINION MINING

Abstract View PDF Download PDF

##plugins.themes.academic_pro.article.main##

Thet Thet Aung
Myat Mon Khaing
Khin Shin Thant
Hlaing Htake Khaung Tin

Abstract

At the present days, COVID-19 (Coronavirus) affections are spreading throughout the world from the beginning of affection of the town of Wuhan in China.  Almost the whole world including many countries are facing difficulties. In Southeast Asia Region, schools, universities, industries, workshops, minimarkets and supermarkets are temporarily closed, and instructions are announced such as wash your hands, stay at home and use mask if people go outside on 24.3.2020. So people watch TV Channels, right sites on Social media and WHO information to know this disease’s update news without going outside. This paper mines reviews of user comments on WHO Southeast Asia Region Organization (WHO SERO) page on Facebook media from 24.3.2020 to 31.5.2020. Sentiment analysis is a technique to classify user’s opinion or emotions about specific domain and identifies phrases and emotions in a text of some sentiment. Sentiment analysis are classified as objective (facts), positive (happiness, satisfaction of the author) or negative (disappointment, dejection) using Information Gain (IG) method.

##plugins.themes.academic_pro.article.details##

How to Cite
[1]
Thet Thet Aung, Myat Mon Khaing, Khin Shin Thant, and Hlaing Htake Khaung Tin, “SENITMENT ANALYSIS ON WHO SOUTHEAST ASIA REGION ORGANIZATION (WHO SERO) USER COMMENT REVIEW AND OPINION MINING”, IEJRD - International Multidisciplinary Journal, vol. 5, no. ICIPPS, p. 8, Jun. 2020.

References

  1. Santhosh Kumar K L, Jayanti Desai, Jharna Majumdar, “Opinion Mining and Sentiment Analysis on Customer Review”, 2016.
  2. Yi-Ching Zeng, Tsun Ku, Shinh-Hung Wu, ”Modeling the Helpful Opinion Mining of Online Consumer Reviews as a Classification Problem”,2014.
  3. Meenambigai B, “An Efficient Surveillanecs of Products Based on Opinion Mining”, 2014.
  4. Yoosin Kim, Seung Ryul Jeong, Imran Ghani, ”Text Opinion Mining to Analyze News for Stock Market Prediction”, 2014.
  5. Nidhi R. Sharma, Prof. Vidya D. Chitre, “ Opinion Mining, Analysis and its Challenges”. 2014

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.