Cognitive Linguistics and Religious Language

Richardson, P. D.; Mueller, Charles M.; Pihlaja, Stephen

doi:10.4324/9781003041139

Cited by 12 publications

(7 citation statements)

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“…Silver et al [29] stated that a sense of agency also encompassed the responsibility felt due to actions undertaken and the effects they have. Therefore, social agency could be uncovered by examining grammatical agency [24][25][26].…”

Section: Grammatical and Social Agencymentioning

confidence: 99%

“…Grammatically, Leslie [25] defined an agent as an entity with an internal source of energy through which it exerted force to carry out the activities referred to in the text. Expanding on this, Richardson et al [24] stated that agency in linguistics is often explored by examining how it is emphasized, manipulated, or concealed. As such, transitivity analysis-the examination of agency in the text-examined the use of active and passive voice or nominalization, where verbs were the word class converted to nouns.…”

Section: Grammatical and Social Agencymentioning

confidence: 99%

“…Through the analysis of transitivity in the 14,425 concordance lines considered, the collocations of "app" and "by the app" and CDA-informed analysis of agency and responsibility, underpinned by SAR, we identified 5 main categories that the active presentations of the app fall into: informing (21.47%), instructing (15.33%), providing permission (9.1%), disrupting (5.02%), and functioning (49.07%). The first 4 categories show the app to be personalized [27] and to make decisions independently [24]. Meanwhile, functioning included instances of the app acting autonomously but also simply functioning as intended or designed to do.…”

Section: Overviewmentioning

confidence: 99%

“…Agency expressed on social media can be investigated in multiple ways, such as through interview or observation [22,23]. We purposefully used corpus linguistics (CL)-informed and critical discourse analysis (CDA)-informed approaches to examine the relationship between grammatical agency and social agency [24]. Grammatical agency, or transitivity, can show whether an entity is presented actively performing an action or passively having an action performed onto them [25].…”

Section: Introductionmentioning

confidence: 99%

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Perceptions of the Agency and Responsibility of the NHS COVID-19 App on Twitter: Critical Discourse Analysis

Heaton,

Nichele,

Clos

et al. 2024

J Med Internet Res

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Background Since September 2020, the National Health Service (NHS) COVID-19 contact-tracing app has been used to mitigate the spread of COVID-19 in the United Kingdom. Since its launch, this app has been a part of the discussion regarding the perceived social agency of decision-making algorithms. On the social media website Twitter, a plethora of views about the app have been found but only analyzed for sentiment and topic trajectories thus far, leaving the perceived social agency of the app underexplored. Objective We aimed to examine the discussion of social agency in social media public discourse regarding algorithm-operated decisions, particularly when the artificial intelligence agency responsible for specific information systems is not openly disclosed in an example such as the COVID-19 contact-tracing app. To do this, we analyzed the presentation of the NHS COVID-19 App on Twitter, focusing on the portrayal of social agency and the impact of its deployment on society. We also aimed to discover what the presentation of social agents communicates about the perceived responsibility of the app. Methods Using corpus linguistics and critical discourse analysis, underpinned by social actor representation, we used the link between grammatical and social agency and analyzed a corpus of 118,316 tweets from September 2020 to July 2021 to see whether the app was portrayed as a social actor. Results We found that active presentations of the app—seen mainly through personalization and agency metaphor—dominated the discourse. The app was presented as a social actor in 96% of the cases considered and grew in proportion to passive presentations over time. These active presentations showed the app to be a social actor in 5 main ways: informing, instructing, providing permission, disrupting, and functioning. We found a small number of occasions on which the app was presented passively through backgrounding and exclusion. Conclusions Twitter users presented the NHS COVID-19 App as an active social actor with a clear sense of social agency. The study also revealed that Twitter users perceived the app as responsible for their welfare, particularly when it provided instructions or permission, and this perception remained consistent throughout the discourse, particularly during significant events. Overall, this study contributes to understanding how social agency is discussed in social media discourse related to algorithmic-operated decisions This research offers valuable insights into public perceptions of decision-making digital contact-tracing health care technologies and their perceptions on the web, which, even in a postpandemic world, may shed light on how the public might respond to forthcoming interventions.

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Section: Grammatical and Social Agencymentioning

confidence: 99%

Section: Grammatical and Social Agencymentioning

confidence: 99%

Section: Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Perceptions of the Agency and Responsibility of the NHS COVID-19 App on Twitter: Critical Discourse Analysis

Heaton,

Nichele,

Clos

et al. 2024

J Med Internet Res

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“…More specifically, Leslie defines an agent as an entity with an internal source of energy through which it exerts force supposedly to carry out the action referred in the text [59]. Expanding on this, Richardson et al state that that agency in linguistics is often explored by examining how it is emphasized, manipulated, or concealed [60]. As such, transitivity analysis -the examination of agency in text-looks at the use of active and passive voice or the nominalization, where verbs are word class converted to nouns.…”

Section: Using Critical Discourse Analysis To Examine Social Mediamentioning

confidence: 99%

“The algorithm will screw you”: Blame, social actors and the 2020 A Level results algorithm on Twitter

Heaton¹,

Nichele²,

Clos³

et al. 2023

PLoS ONE

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In August 2020, the UK government and regulation body Ofqual replaced school examinations with automatically computed A Level grades in England and Wales. This algorithm factored in school attainment in each subject over the previous three years. Government officials initially stated that the algorithm was used to combat grade inflation. After public outcry, teacher assessment grades used instead. Views concerning who was to blame for this scandal were expressed on the social media website Twitter. While previous work used NLP-based opinion mining computational linguistic tools to analyse this discourse, shortcomings included accuracy issues, difficulties in interpretation and limited conclusions on who authors blamed. Thus, we chose to complement this research by analysing 18,239 tweets relating to the A Level algorithm using Corpus Linguistics (CL) and Critical Discourse Analysis (CDA), underpinned by social actor representation. We examined how blame was attributed to different entities who were presented as social actors or having social agency. Through analysing transitivity in this discourse, we found the algorithm itself, the UK government and Ofqual were all implicated as potentially responsible as social actors through active agency, agency metaphor possession and instances of passive constructions. According to our results, students were found to have limited blame through the same analysis. We discuss how this builds upon existing research where the algorithm is implicated and how such a wide range of constructions obscure blame. Methodologically, we demonstrated that CL and CDA complement existing NLP-based computational linguistic tools in researching the 2020 A Level algorithm; however, there is further scope for how these approaches can be used in an iterative manner.

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Giovanelli

2022

The Language of Siegfried Sassoon

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Cognitive Linguistics and Religious Language

Cited by 12 publications

References 0 publications

Perceptions of the Agency and Responsibility of the NHS COVID-19 App on Twitter: Critical Discourse Analysis

Perceptions of the Agency and Responsibility of the NHS COVID-19 App on Twitter: Critical Discourse Analysis

“The algorithm will screw you”: Blame, social actors and the 2020 A Level results algorithm on Twitter

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