Common frames for conceptualizing mental illness in news media and their effect on public attitudes

对精神疾病的污名化态度构成了一个重大的社会问题，其不利影响渗透到受影响者生活的各个领域。除其他外，耻辱感导致获得医疗服务的障碍和继续接受治疗的可能性降低（Corrigan et al. 2014），难以获得和保持就业（Corrigan and Watson 2002）以及社区环境中的社会距离增加（Henderson et al. 2016）。根据污名呐喊调查，90%的服务使用者认为污名对他们的生活产生了负面影响（“是时候改变了”，2008年）。迄今为止，英国最大的反耻辱运动是“是时候改变”运动。到目前为止，“改变的时间”分三个阶段（2007-2011年；2011-2015年；2016-2021年）进行，重点是消除对精神疾病的污名化。虽然这一运动有助于改变人们对精神疾病的态度，但为了成功和持久地减少耻辱感，需要进一步研究精神疾病是如何在公共话语中构建的，以及某些精神疾病的话语框架以何种方式促成了不同的态度。在这个项目中，我将通过开发基于语料库的方法来识别话语中出现的隐喻，研究在“时间改变”运动之前和期间，大众媒体中用于构建精神疾病的语言，以及这种语言如何实例化和影响人们的态度。目前，反污名运动的效果主要通过态度调查来衡量（Rossetto等人，2019）。态度调查对于衡量态度是有问题的，因为参与者往往倾向于歪曲自己（例如，看起来更有利），而且几乎不可能获得不太公开的态度，例如隐性耻辱（Stull等人，2013）。一种间接衡量公众态度的方法是通过隐喻。从本质上讲，隐喻是用一个领域（目标领域）来构建另一个领域（源领域），从而突出目标领域的某些方面，同时隐藏其他方面（Lakoff和Johnson， 1980）。在最近的研究中，这被描述为隐喻的“框架能力”（Semino, Demjen, Demmen, 2016）。就态度而言，这使得隐喻成为研究通过语言表达的精神疾病的内隐概念化的有力工具。然而，为了有效地研究公众态度，有必要利用大量的数据，这就需要开发基于语料库的方法。本研究的目的是：-开发一种基于语料库的半自动方法，用于大规模识别和跟踪话语中系统隐喻的使用-将该方法应用于媒体话语的大型语料库，并在“改变时间”运动之前和期间识别常见的隐喻及其框架能力-在实验环境中评估主导框架和隐喻对话语参与者态度的影响。本项目将涉及开发基于语料库的隐喻识别和分析及其框架效应的新方法，并将其应用于新闻中对精神疾病的描述。这将有助于更好地理解英国精神疾病的语言结构是如何随着时间的推移而变化的，特别是在“时间改变”反污名运动之前和期间。最终，这项研究可以用来改善未来的反污名运动，也可以根据他们的语言行为来衡量公众对各种问题的态度。

Stigmatizing attitudes towards mental illness pose a significant societal problem and its adverse effects permeate all areas of life for those affected. Among others, stigma leads to barriers in accessing care and a decreased likelihood of remaining in treatment (Corrigan et al. 2014), difficulty obtaining and retaining employment (Corrigan and Watson 2002) as well as increased social distance in community settings (Henderson et al. 2016). According to the Stigma Shout survey, 9 in 10 service users feel that stigmatization is negatively affecting their lives ('Time to Change', 2008). The largest anti-stigma campaign in England to date is the 'Time to Change' campaign. 'Time to Change' has so far operated in three phases (2007-2011; 2011-2015; 2016-2021) and focuses on de-stigmatizing mental. While this campaign has contributed to changing attitudes towards mental illness, in order to decrease stigma successfully and lastingly, there needs to be further research into how mental illness is constructed in public disocurse and in what ways certain discursive framings of mental illness contribute to different attitudes.In this project I will examine the language used to construct mental illness in mass media before and during the 'Time to Change' campaign, and how this language instantiates and affects attitudes, by developing corpus-based methods to identify metaphors as they emerge in discourse. Currently, the effect of anti-stigma campaigns is predominantly measured using attitude surveys (Rossetto et al., 2019). Attitude surveys are problematic for measuring attitudes because participants are often inclined to misrepresent themselves (e.g. to appear more favourably) and it is virtually impossible to access less overt attitudes, such as implicit stigma (Stull et al., 2013). One way to indirectly gauge public attitudes is through metaphor. Essentially, metaphors structure one domain (target domain) in terms of another (source domain), thereby highlighting certain aspects in the target domain, while hiding others (Lakoff and Johnson, 1980). In more recent work, this has been described as the 'framing power' of metaphor (Semino, Demjen, Demmen, 2016). Regarding attitudes, this makes metaphor a powerful tool in both investigating implicit conceptualizations of mental illness expressed through language. However, to study public attitudes effectively, it is necessary to draw on large amounts of data, which requires the development of corpus-based methods.The aims of this research are:- to develop to develop a corpus-based semi-automatic method for large-scale identification and tracking of systematic metaphor use in discourse- to apply this method to a large corpus of media discourse and identify common metaphors and their framing power before and during the phases of the 'Time to Change' campaign- to evaluate the effects of dominant frames and metaphors on attitudes of discourse participants in an experimental settingOverall, this project will involve the development of novel methods for the corpus-based identification and analysis of metaphors and their framing effects and apply this to the portrayal of mental illness in the news. It will contribute to a better understanding of how the linguistic construction of mental illness in the UK has changed over time, especially before and during the 'Time to Change' anti-stigma campaign. Ultimately, this research can be utilized to improve future anti-stigma campaigns, but also in general to gauge public attitudes towards various issues on basis of their language behaviour.