Author(s):
1. Matthew R. Maulion:
University of Science and Technology of Southern Philippines, Lapasan, Cagayan de Oro City 9000, Philippines
2. Adrian M. Perez:
De La Salle University, 2401 Taft Avenue, Manila, Philippines
Abstract:
The ABS-CBN shutdown last May 5, 2020, took a toll in the Philippine media industry. Given this incident, the study intends to determine if significant changes can be detected in the manner that articles were written before and after the ABS-CBN shutdown. Its significance is to determine using natural language processing (NLP) methods if censorship or a sudden event (i.e. a media giant shutdown) can influence the way news is written and published. Articles before and after the shutdown from two primary news sources were chosen, ranging from three months before and after the actual shutdown date. Preprocessing and cleaning were carried out in order to perform sentiment analysis and topic modeling. Results were compared across the two timeframes and across the two sources. Notable shifts in the dominant topics discussed by each source were detected for both timeframes, with topics disappearing and emerging after the shutdown. Furthermore, shifts in sentiment scores were also detected across both sources with evident changes in polarity for some uncovered topics. It is recommended for future work to make the analysis more granular by incorporating page views and conducting an in-depth content assessment through paragraphs and sentences.
Page(s):
529-533
DOI:
DOI not available
Published:
Journal: Science International, Volume: 34, Issue: 6, Year: 2022
Keywords:
News Media
,
Sentiment analysis
,
Topic Modelling
,
natural language processing
References:
References are not available for this document.
Citations
Citations are not available for this document.