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Analyzing the Discussion of Gregorio Murder on Twitter using Text Mining Approach

February 2021

DOI:10.13140/RG.2.2.13322.80322

Authors:

Merimee Tampus Siena

Ateneo de Manila University

Preprints and early-stage research may not have been peer reviewed yet.

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Analyzing the Discussion of Gregorio Murder on Twitter using Text Mining Approach

Merimee T. Siena

Psychology Department, Ateneo De Manila University

Office of Student Affairs and Student Services, Philippine Normal University

Corresponding Author’s Address: 38 T Concepcion St. Cooperative, Marulas Valuenzuela City,

Philippines, 1440

Email Address: merimee.tampus-siena@obf.ateneo.edu

Abstract

Using text mining approach, this study explored the common themes surrounding the

social media users’ discussions regarding the recent killing of Sonya and Frank Gregorio which

sparked conversation on Twitter in the Philippines. Using keywords from the trending hashtags

#StopKillingsPH and #JusticeforSonyaGregorio, tweets were extracted via Python program. A

total of 1,045 tweets from December 21 to December 28, 2020 were collected and analyzed in

terms of frequency, sentiment, subjectivity, and surrounding themes. Results show that

discussions regarding the Gregorio murder revolved on the netizen’s call for justice, demand that

the suspect be charged with murder, and an online petition and a louder plea to stop killings and

end police brutality in the country. Finally, this study may show how social media can be

influential in mobilizing the authorities to act against injustices in the Philippines and in affecting

change in the society.

Keywords: Text Mining, Twitter, Social Media, Philippines

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