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

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

Opinion to Emotion Mining: A Sentiment Analysis towards Super Typhoon 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 Supertyphoon Ompong has been considered a powerful typhoon that struck the island of Luzon on 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 phenomenon. 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 a word cloud.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
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