Opinion to Emotion Mining: A Sentiment Analysis towards Super Typhoon Ompong

Albert  Vinluan; Mamerto T.  Goneda; Francis Arlando L.  Atienza; John Paul P.  Miranda; Rolando R.  Fajardo; Dominic C.  Cabauatan

doi:10.31149/ijot.v3i5.1779

Albert Vinluan University of the East, Manila
Mamerto T. Goneda University of the East, Manila
Francis Arlando L. Atienza University of the East, Manila
John Paul P. Miranda University of the East, Manila
Rolando R. Fajardo University of the East, Manila
Dominic C. Cabauatan University of the East, Manila

DOI: https://doi.org/10.31149/ijot.v3i5.1779

Keywords: Opinion Mining, Emotion Mining, Ompong

Abstract

Twitter as one of the microblogging websites has gained its popularity dues to ease sharing of contents in various forms, which include text, images and links. Social media users post and share real time messages about their opinions or comments on a variety of topics, express their typhoon. The Super typhoon Ompong has been considered as powerful typhoon that struck the Island of Luzon September 15, 2018. It has been the strongest typhoon to strike Luzon since Typhoon Megi in 2010. With this, many tweets have been generated expressing people’s real time reactions and opinions whether it is positive, negative or neutral regarding this phenomena. Owing to the increasing high coverage and impact of Twitter, opinions of people on some issues and their emotion towards the super typhoon ompong were shared through social media can be significantly influenced. It is in this context, that the researchers conducted this study to perform the opinion to emotion mining based on the sentiment analysis towards super typhoon ompong were data was generated and collected through a post and message on twitter. Specifically, it sought to determine the sentiments before, during and after the landfall; and perform data visualization using word cloud.

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