Linguistic Landscape - Volume 10, Issue 4, 2024

This paper investigates the Linguistic Landscape (LL) of Leni Robredo’s 2022 presidential campaign rallies in the Philippines and explores the role of gender and sexuality in constructing prefigurative spaces within the offline-online nexus. Through artifacts used during the campaign, the paper examines how Robredo supporters utilize semiotic resources and intertextual references from popular and meme culture as well as LGBTQ+ media to adopt stances vis-à-vis gender and sexuality. The paper suggests that the aggregation of these stances elicit affects that facilitate a prefigurative genderscape where participants enact an ethos of hope. While these practices cannot completely transcend entrenched forms of power (e.g., macho populism and dynastic democracy), they materialize a potential future characterized by a people-driven movement. The paper proposes a future direction for LL studies: engaging prefigurative politics in the examination of the emergent spaces that respond to increasing precarity and sociopolitical upheavals.

The Hawaiian monk seal is the most endangered of all pinnipeds (walruses, sea lions, and seals). The threat of extinction has loomed large for these seals, especially as sea-level rise threatens to inundate their primary habitat, but an alliance of conservation actors, from federal agencies to non-profit volunteer groups, are working to bring this species back from the brink in Hawai‘i. Today, the monk seal population is finally beginning to recover, but as monk seals make a comeback and reclaim busy beaches, new and unpredictable human relationships with monk seals are taking shape in an uncertain time of climate change. Drawing on data from my ethnographic research of the monk seal-human contact zone in Hawai‘i, in this article, I explore possibilities for a multispecies approach to linguistic and semiotic Landscape research that seeks to ‘multiply’ our understanding of social life and meaning-making in public space as a rich, multispecies entanglement.

This article explores applications of artificial intelligence (AI) technologies in Linguistic Landscape research. Traditionally, LL research has relied on manual data collection and analysis, often involving photographs of public signage, advertisements, and other visual language displays. However, this manual approach can present challenges, including time-consuming data collection, inconsistent data quality, and potential researcher bias. Two AI technologies in particular hold promise for addressing these challenges in LL research: computer vision (CV) and large language models (LLMs). CV automates the identification and extraction of text from images, improving data accuracy and enabling large-scale image analysis. LLMs, based on natural language processing, can detect, translate, and interpret multilingual text. This article explores the affordances and challenges of using AI technologies in LL research and discusses methods to improve data collection, enhance accuracy, and support the analysis of multilingual environments. It also raises ethical issues and limitations of the technologies.

Datafication, or the translation of our everyday actions into quantifiable metrics, underwrites a wide set of contemporary discursive practices. With a specific focus on the social media platform Instagram, this paper analyzes mediatized landscape signs as ‘datafied discourse’ enmeshed in an entangled apparatus of platforms, algorithms, and online networks. Using a corpus of 404 public Instagram posts gathered from the Café de Flore geotag, I examine how the vernacular practices of geotagging, mediatization, and remediatization reflexively construct this ostensibly ‘user-generated’ landscape. I then consider the implications of these and other discursive practices occurring at the ‘online-offline nexus’ through the dimensions of authorship and ownership. Finally, amid a confluence of new LL work, I propose to orient scholarship toward an ‘infrastructural’ perspective, in which datafication, online platforms, and algorithms are understood to exert considerable influence over our landscapes, thus emerging as relevant to scholars engaged in any genre of LL analysis.