Main Article Content

Abstract

This study analyses the sentiment polarity of the banner headlines from six broadsheets in the Philippines with the biggest circulation nationwide. The sentiment polarity is the general perception of whether it is worded positively, neutral, or negatively. This study employs five machine learning and artificial intelligence (AI) to conduct the analysis. The results reveal a tone reflecting editorial policy that tends to lean towards the negative tone. While there is a utility for negative framing of the news, this paper argues that a pivot to the positive, particularly in the Philippine setting, is worth considering. Based on current literature, positivity shows the potential to bring in more readers. Publishers can leverage positivity in the news as part of strategies to stem the tide of readership decline. Positivity in the news should start with the headline, through which readers have a first glimpse of the story.

 

Keywords: sentiment polarity identification, sentiment analysis, sentiment polarity of banner headlines

Article Details

Author Biography

Manuel Jr Diaz, West Philippine Sea Institute, Philippines

The author is corresponding fellow at West Philippine Sea Institute. He served as Dean, College of Computer Studies, Ateneo de Naga University in Naga City, Philippines, where he has also taught in the computer science, information technology, information management, and the digital arts and computer animation programs. He earned his BSc in Physics and BSc in Computer Engineering at the Ateneo de Manila University (Quezon City, Philippines), Master in Information Technology at Charles Sturt University (NSW Australia), Juris Doctor at University of Nueva Caceres (Naga City, Philippines), and Graduate Certificate in Research Methods and Design at University of Canberra (ACT Australia).
How to Cite
Diaz, M. J. (2021). Sentiment Polarity Identification in Banner Headlines of Broadsheets in the Philippines. Asian Journal of Media and Communication, 5(2). https://doi.org/10.20885/asjmc.vol5.iss2.art1