Sentiment Analysis on Kto12 Program Implementation in the Philippines

Abstract

In the Philippines, Kto12 program seems praiseworthy and auspicious, yet it faces some academic, social and economic issues which may be the time to address that problems and issues. Using sentiment analysis, the opinions and sentiments of the Filipino citizens shall be heard and shall then be addressed. In this study, descriptive research method was used to describe the behaviour and variation of sentiments from the dataset of related tweets on Kto12 program implementation which was collected and labelled whether positive or negative sentiments for future analysis. The researchers used the dataset of tweets from 2012 up to 2016 that was collected using python command GetOldTweets. Machine learning software was used to validate manually annotated datasets that resulted with high percentage of correctly classified instances using Support Vector Machine (SVM). Quantitative research method was used in this study to compare and analyse the sentiments’ variation from 2012 up to 2016. There are 64% positive sentiments compared to 36% negative sentiments out of the total 100% sentiments. This study shall help the Philippine government particularly the Department of Education and Commission on Higher Education to be aware of the citizens’ sentiments, as such, possible reviews and improvement of curriculum and program design should also be conducted. Some interventions should also be performed to enhance and have concrete and comprehensive program for basic and higher education.