Metaphorical Framing of Refugees, Asylum Seekers and Immigrants in UK s Left and Right-Wing Media (2024)

Abstract: The metaphorical framing of refugees, asylum seekers, and immigrants (RASIM) has been widely explored in academia, but mainly through close analysis. The present research outlines a large-scale computational investigation of RASIM metaphors in UKs media discourse. We experiment with a method that facilitates automatic identification of RASIM metaphors in 21 years of RASIM-related news reports from eight popular UK newspapers. From the metaphors extracted, four overarching frames are identified. Further analysis reveals correlations between political bias and metaphor usage: overall, right-biased newspapers use RASIM metaphors more frequently than their left-biased counterparts. Within the metaphorical frames, water, disaster, and non-human metaphors are more prevalent in right-biased media. Additionally, diachronic analysis illustrates that the distinctions between left and right media have evolved over time. Water metaphors, for example, have become increasingly more representative of the political right in the past two decades.

## introduction issues regarding refugees, asylum seekers, and immigrants (henceforth rasim) have been widely debated for their social, cultural, and economic implications. metaphors, in particular, have received much scrutiny for their ability to link conceptualizations of immigration to personal and cultural experiences. as repositories of cultural understandings, they allow dominant ideologies and prejudices to be represented and reinforced in a transparent fashion, shaping public opinion without drawing attention to themselves @xcite . discussions concerning the metaphorical framing of immigrants, especially in political and media discourse, have primarily been carried out under the critical discourse analysis (cda) framework @xcite @xcite @xcite @xcite . most of the metaphors identified and discussed so far represent dehumanizing or stigmatizing frames for immigrants and refugees, such as animals @xcite , diseases @xcite , enemies and invaders @xcite , pollution @xcite , or other destructive forces like flood @xcite . another point of interest lies in how metaphors may be connected to the ideological compositions of texts @xcite . @xcite , for example, observes differences between uk's centre-right and far-right discourses in terms of their use of immigration metaphors, arguing that they contribute to the formation of legitimacy in right-wing political communication. however, this analysis does not cover data from left-wing media. partly due to the complexity of metaphorical language, most research in this field so far has relied on close analysis of small datasets. in this research, we conduct a large-scale computational investigation into the metaphorical framing of rasim in british media. our data comprises rasim-related articles published in eight prominent uk newspapers over a span of 21 years from 2000 to 2020. from the text material, metaphorical expressions related to rasim are automatically identified using both construction pattern matching and a finetuned roberta model. the main research questions can be outlined as: (1) how have rasim been metaphorically framed in the uk media? (2) are distinctions among the newspapers' political stances reflected in their use of rasim metaphors? in summary, by incorporating computational methods in the analysis of rasim metaphors, we aim to move beyond the limitations of small-scale studies, exploring how metaphors contribute to shaping public perceptions and investigating potential connections between metaphorical language and political stance. ## related work traditionally, analysis of metaphors in naturally occurring language has relied primarily on close examination of small datasets. with the development of corpus tools and the increasing accessibility of large corpora, corpus methods have been employed to extend such analysis to a greater scale @xcite @xcite @xcite . most research in this direction has taken a lexical approach by analyzing concordances of several specific search terms, defined either by drawing upon the researcher's knowledge of the source and target domains, or through close analysis of a sample of the corpus @xcite . however, this method has an inherent limitation -it confines the analysis to predetermined search strings, making it challenging to identify new metaphorical patterns @xcite . a more sophisticated approach involves the use of wmatrix @xcite , a corpus tool capable of assigning tokens to semantic domains based on the ucrel semantic annotation scheme (usas). initially put forward by @xcite , this method builds upon the assumption that semantic tags allocated by wmatrix correspond to the source domains of metaphoric expressions. instead of searching for specific word terms, this approach seeks domain tags, enabling the discovery of a broader spectrum of metaphors beyond predefined word lists. @xcite start by identifying a list of metaphorical expressions from a small sample of the entire corpus, from which source domains and corresponding usas tags are derived for query and analysis. similarly, @xcite follows a similar procedure to identify metaphors in promotional tourism discourse. however, since the usas tagger itself cannot make predictions about metaphoricity, extensive human efforts are still required for disambiguating the candidate metaphors, which is not ideal for larger datasets. within computational linguistics, automatic identification and interpretation of metaphors have been a challenging and widely discussed topic (e.g., @xcite @xcite . in recent years, efforts have been made to incorporate such advancements in the analysis of metaphorical framing in public discourse. @xcite , for example, put forward a computational framework for investigating the dehumanization of lgbtq people in the new york times articles. recognizing vermin metaphors as an important component of dehumanization, the authors use word embeddings to measure the metaphorical relationship between lgbtq people and vermin. specifically, a vermin concept vector is calculated by averaging the vectors of a predefined list of vermin terms. the intuition is that, the more closely a group is related to vermin through metaphors, the larger the cosine similarity will be between the group label vector and the vermin vector. in a similar vein, @xcite investigate how republicans and democrats frame immigrants differently using dehumanizing metaphors such as "animal" and "cargo". in order to detect implicit metaphorical language, mentions of immigrants and immigrant groups are masked from the sentences. a neural language model, bert @xcite , is then used to predict the mask words based on the surrounding contexts. from bert's predictions, metaphoricity is calculated from the probabilities assigned to terms related to the predefined source domains. in this way, they essentially measure how much mentions of immigrants "sound like" particular types of dehumanizing metaphors. in order to provide a comprehensive account of the metaphorical language related to rasim, we hope that our identification system should be capable of unveiling novel metaphorical expressions, rather than relying on a fixed set of keywords or key domains. for this purpose, we experiment with a system based on finetuning roberta, a transformer-based language model capable of encoding nuanced contextual information. the setup is further introduced in section 3.2. ## conclusions in this research, we utilized a computational approach to analyze 21 years of uk news reports on refugees, asylum seekers, and immigrants (rasim), revealing four key metaphorical frames: water, disaster, non-human, and enemy. overall, the metaphorical representation of rasim in british media has been predominantly stigmatizing and dehumanizing. further analysis shows a correlation between political bias and rasim metaphors: while both left-and right-wing newspapers exhibit increased metaphorical language when discussing rasim compared to "citizen", this difference is more pronounced in right-wing discourse. investigations of individual frames reveal that the dehumanizing frames are generally more common in right-biased media. additionally, such connec-tions have changed over time. water metaphors, for example, have become increasingly more representative of the political right in the past two decades. such divergences can be illustrative of the broad ideological stances on immigration. with the help of computational modelling, we were able to extend the analysis of metaphorical framing to a large dataset, enabling a broader account of the interplay between language and ideology. this scaling-up, however, comes with trade-offs. first, we had to restrict ourselves to a closed set of syntactic structures, which is far from enough to fully address the richness and flexibility of metaphorical expressions in real life. how to strike a balance between the need for formalization and the high variability of real-world language can be a challenge for similar research. second, to better understand how the use of metaphors relates and contributes to the sociopolitical environment, it can be important to examine the specific contexts, such as the event being described or the attitude of the authors. however, as we have only focused on individual metaphorical words, such contextual information has not been taken into consideration. future research can therefore seek to establish links between text and context for a more nuanced analysis of language as a social practice.