“Sana All” presupposed Empathy: Netizen’s General Perceived Performance of the Government responses to COVID-19

Abstract

People in social media platforms who shared opinions, known as netizens, posted contradicting perceptions against the satisfactory results released by research agencies about the government's responses to COVID-19. In this study, social media-Twitter, which is one of the key communication channels, was the main source of the data to explore the public's perception about the Philippine government's responses to the pandemic. To limit the tweets to be studied, sana all, being the popular language phenomenon used during the community quarantine, was observed and utilized as a code to be generated in the Twitter search engine. Sana all is a Filipino unique expression that calls for equality or literally means hope (sana) of the speaker for everyone (all). Like it was previously associated in the Filipino concept of inggit (envy), this study somehow expounds the investigation of this season's well-used phrase. A number of 257 tweets were collected from March to August 2020. To maximize the richness of the contents of each tweet collected, the researchers used presuppositions to extract inferences such as the background information of the typewritten text that can be found in word, phrase, and sentence in the tweets. Then, presupposed data were coded, grouped, and labeled by their observed commonalities, producing 11 categories: opinions to current governance, observed social inequalities, comments on national policies, polarized political positions, impact of pandemic on citizens, people's general aspirations, support to the most vulnerable groups, concern to exhibit good citizenship, heroic deeds of front liners, public's trust to systems, and resiliency. The overall language attitude observed from the presupposed tweets is empathy. This paper will discuss how empathy associates the sound dissatisfaction of the netizens to the responses made by the current administration to combat the COVID-19 multiple effects.