Multilinguals Write Back : Modeling Language, Politics and Identity in Philippine Social Media Frances Cruz University of Antwerp, University of the Philippines Abstract Introduction Methodology Results and Discussion Conclusion References The Philippines is a multilingual country with estimates of up to 134 languages (KWF, 2014). Despite this linguistic diversity, the country’s languages are disproportionally represented in print media. While national broadsheets are primarily published in English, Filipino and regional languages tend to be the language of tabloids, reflecting relationships between print media type, language, and class (Ables, 2003, p. 44-45). Social media, with its multilingual digital publics, can thus give insights into different languages’ current degree of use in written discourse. This study documents the intersections of language and the public sphere through a cross- sectional model of comments on public Facebook (FB) pages of selected Philippine newspapers from 2015-2019. Its objectives are to train a multilabel classifier to model monolingual and code- switched language use in discussions of current events, identify differences between national and regional newspapers, and glean digital insights into the conduct of public discourse. • Codeswitching was a discernible feature of online texts. • Monolingual texts in Tagalog/Filipino were the most common, followed by monolingual English entries and Cebuano/Bisaya entries. • Among the national newspapers, results from the Inquirer and Philippine Star indicated the presence of more Tagalog/Filipino than English comments, with the Manila Bulletin and Manila Times showing the opposite trend. • In terms of regional newspapers, Cebuano/Bisaya comments in Cebu-based newspapers Cebu Daily News and Sun Star Cebu outnumbered English and Tagalog/Filipino comments. • Two Mindanao-based newspapers, Mindanao Times and Sun Star Davao, featured Tagalog/Filipino as the most-used language, followed by English and Cebuano/Bisaya. Ables, H. (2003). Mass Communication and Philippine Society. University of the Philippines Press. Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Proceedings of NAACL-HLT, 4171–4186. Jünger, J., & Keyling, T. (2019). Facepager: An application for automated data retrieval on the web. https://github.com/strohne/Facepager/. Komisyon saWikang Filipino (2014). Atlas Filipinas. https://kwf.gov.ph/atlas-filipinas. Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Bertrand, T., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., David Cournapeau, Brucher, M., Perro, M., & Duchesnay, E. (2011). Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research, 12, 2825–2830. Selected Newspapers’ FB Pages: Manila Bulletin, Manila Times, the Philippine Daily Inquirer, the Philippine Star, Cebu Daily News, Mindanews, Mindanao Times, Sun Star Cebu, Sun Star Davao, and The Freeman were captured by Facepager (Jünger & Keyling 2019). Data Scope: Two months per newspaper in 2015, 2017 and 2019. Classifier: A multilabel classifier in the form of a random forest (RF) (Pedregosa et al., 2011) was finetuned on top of a pretrained BERT feature extractor (specifically the ‘bert-base-multilingual- uncased’ model) (Devlin et al., 2019). Test and Training Set: Over 16,000 social media comments were annotated for the presence/absence of Tagalog/Filipino, Cebuano/Bisaya and English respectively. • In terms of social media responses, regional newspapers offer more diverse language use. • Despite the presence of English-language newspapers, current events are written about and responded to by a multilingual Philippine public sphere. • Social media thus offers opportunities not only for re-thinking monolingual norms in media, but may also revitalize written forms of regional languages. Figure 5: Language use as percentage of