Semantic Equivalence of Algospeak as a Register in Social Media based on Semantic Prosody Theory

Abstract

The phenomenon of algospeak usage in social media reflects the emergence of linguistic masking strategies that enable negatively toned messages to be conveyed implicitly while remaining concealed from algorithmic monitoring systems. A review of the literature indicates that empirical approaches remain limited in examining the visual forms of algospeak disguises that are increasingly widespread in digital discourse, as well as their impact on the original meanings of the words involved. Therefore, this study was conducted to identify the categories of word types commonly disguised to represent negative human traits and to examine the semantic equivalence between algospeak disguised forms and their original lexical forms through the lens semantic prosody theory. A total of 5,000 public comments from Facebook were extracted using the PhantomBuster application as the primary data source. Data collection was carried out through an Application Programming Interface (API) supported by an automated script specifically developed to systematically extract user comments. The analysis was conducted qualitatively through open coding and thematic analysis, followed by the application of semantic prosody theory with an emphasis on collocational patterns and evaluative meanings underlying the utterances. The findings reveal that social media users tend to target individual weaknesses in physical, moral, intellectual, social, and ideological domains through algospeak forms, such as “l3mb00”, “p3ny0nd0l”, and “m4c41 p0l1t!k”. Nevertheless, the results demonstrate that orthographic transformations do not weaken the semantic force of the original words, as the accompanying collocational and evaluative contexts consistently preserve their implicit meanings. Overall, the application of semantic prosody theory proves effective in addressing ambiguity in disguised language and contributes to the empirical and contextualised advancement of digital semantic discourse, particularly by providing a methodological foundation for analysing lexical masking strategies on social media, as well as offering practical guidance for digital linguistics research, language education, and digital content management.

Keywords: Algospeak, implicit meaning, semantic prosody, social media, collocation, linguistic masking

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