Using the Twitter Data Classifier Web Application (TDCWA) to Identify Social Issues for the Philippines’ Synod of Synodalities

 Religion and Social Communication 21, no. 1 (2023)

Author

Gian Lloyd B. Jacoba

Abstract 

Social Media has become one of the most reachable platforms for Filipinos to communicate with one another and share news and trending topics being discussed in the Philippines. Therefore, organizations can utilize a vast data collection and processing opportunity to help in their decision-making through Data Analytics and Machine Learning. One of the organizations that can benefit from Data Analytics and Machine Learning is the Roman Catholic Church. As the Church is currently holding its Synod of Synodalities, the Synod needs to be provided with unbiased societal issues that the Church must tackle as it moves towards an uncertain future. The paper offers a Data Analytics and Machine Learning solution using Twitter Data as the primary source of data to be processed. The study first scraped data from Twitter using a data-scraping application called Twint. Overall, 12,000 tweets were collected but had to be preprocessed. Descriptive analytics was utilized to determine the most frequently used words in the collected tweets. The social issues processed by the machine learning algorithm and discussed in the study can be used to augment and support the information already gathered by the Synod. 

Keywords

data analytics, machine learning, Synod of Synodalities, Roman Catholic Church, social issues 

PAGES 29-58

Submitted: February 4, 2023; Accepted: March 19, 2023; Published: May 30, 2023