JOURNAL ARTICLE

Local language in the context of political divides: An evaluation of local language use in a voter-information campaign in the Philippines using Facebook split tests.

  • Published In: Journal of Asian Pacific Communication (John Benjamins Publishing Co.), 2024, v. 34, n. 1. P. 1 1 of 3

  • Database: Communication Source 2 of 3

  • Authored By: Mendoza, Ronald U.; Domingo, Cristine Lian C.; Mendoza, Gabrielle Ann S.; Yap, Jurel K. 3 of 3

Abstract

As populist leaders leverage disparities across geographic and language communities, democracies are threatened by an increasingly divisive political climate that compromises public discussions. This study evaluates how the basic communication strategy of utilizing local languages in information campaigns can help overcome divides by encouraging engagement and discussions. We conduct a field experiment to assess whether using the four most prevalent languages in the Philippines (Cebuano-Bisaya, Ilonggo-Hiligaynon, Ilokano, and Waray-Samarnon) can increase engagement in online materials for targeted linguistic groups. Through split-testing on Facebook, we find evidence that local language materials are more likely to catch the attention of the audience and increase engagement. Qualitative validation shows that local language use is an effective tool to build self-efficacy for linguistic groups to join in on national conversations, and serves as an identity marker to evoke a sense of pride and community. These findings open opportunities for evidence-guided social media campaign strategies. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Asian Pacific Communication (John Benjamins Publishing Co.). 2024/01, Vol. 34, Issue 1, p1
  • Document Type:Article
  • Subject Area:Religion and Philosophy
  • Publication Date:2024
  • ISSN:0957-6851
  • DOI:10.1075/japc.00105.men
  • Accession Number:175368750
  • Copyright Statement:Copyright of Journal of Asian Pacific Communication (John Benjamins Publishing Co.) is the property of John Benjamins Publishing Co. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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