40 research outputs found

    Dashboard of sentiment in Austrian social media during COVID-19

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    To track online emotional expressions of the Austrian population close to real-time during the COVID-19 pandemic, we build a self-updating monitor of emotion dynamics using digital traces from three different data sources. This enables decision makers and the interested public to assess issues such as the attitude towards counter-measures taken during the pandemic and the possible emergence of a (mental) health crisis early on. We use web scraping and API access to retrieve data from the news platform derstandard.at, Twitter and a chat platform for students. We document the technical details of our workflow in order to provide materials for other researchers interested in building a similar tool for different contexts. Automated text analysis allows us to highlight changes of language use during COVID-19 in comparison to a neutral baseline. We use special word clouds to visualize that overall difference. Longitudinally, our time series show spikes in anxiety that can be linked to several events and media reporting. Additionally, we find a marked decrease in anger. The changes last for remarkably long periods of time (up to 12 weeks). We discuss these and more patterns and connect them to the emergence of collective emotions. The interactive dashboard showcasing our data is available online under http://www.mpellert.at/covid19_monitor_austria/. Our work has attracted media attention and is part of an web archive of resources on COVID-19 collected by the Austrian National Library.Comment: 23 pages, 3 figures, 1 tabl

    LEIA: Linguistic Embeddings for the Identification of Affect

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    The wealth of text data generated by social media has enabled new kinds of analysis of emotions with language models. These models are often trained on small and costly datasets of text annotations produced by readers who guess the emotions expressed by others in social media posts. This affects the quality of emotion identification methods due to training data size limitations and noise in the production of labels used in model development. We present LEIA, a model for emotion identification in text that has been trained on a dataset of more than 6 million posts with self-annotated emotion labels for happiness, affection, sadness, anger, and fear. LEIA is based on a word masking method that enhances the learning of emotion words during model pre-training. LEIA achieves macro-F1 values of approximately 73 on three in-domain test datasets, outperforming other supervised and unsupervised methods in a strong benchmark that shows that LEIA generalizes across posts, users, and time periods. We further perform an out-of-domain evaluation on five different datasets of social media and other sources, showing LEIA's robust performance across media, data collection methods, and annotation schemes. Our results show that LEIA generalizes its classification of anger, happiness, and sadness beyond the domain it was trained on. LEIA can be applied in future research to provide better identification of emotions in text from the perspective of the writer. The models produced for this article are publicly available at https://huggingface.co/LEI

    Dementia risk factors modify hubs but leave other connectivity measures unchanged in asymptomatic individuals: a graph theoretical analysis

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    Background: Alzheimer's Disease (AD) is the most common form of dementia with genetic and environmental risk contributing to its development. Graph theoretical analyses of brain networks constructed from structural and functional MRI measurements have identified connectivity changes in AD and individuals with mild cognitive impairment (MCI). However, brain connectivity in asymptomatic individuals at risk of AD remains poorly understood. Methods: We acquired diffusion-weighted magnetic resonance imaging (dMRI) data from 160 asymptomatic individuals (38-71 years) from the Cardiff Ageing and Risk of Dementia Study (CARDS). We calculated white matter tracts and constructed whole-brain, default-mode-network and visual structural brain networks that incorporate multiple structural metrics as edge weights. We then calculated the relationship of three AD risk factors, namely Apolipoprotein-E Δ4 genotype (APOE4), family history (FH) of dementia, and central obesity, on graph theoretical measures and hubs. Results: We observed no risk-related differences in clustering coefficients, characteristic path lengths, eccentricity, diameter and radius across the whole-brain, default-mode-network or visual system. However, a hub in the right paracentral lobule was present in all high-risk groups (FH, APOE4, obese) but absent in low-risk groups (no FH, APOE4-ve, healthy weight). Discussion: We identified no risk-related effects on graph theoretical metrics in the structural brain networks of cognitively healthy individuals. However, high-risk was associated with a hub in the right paracentral lobule, an area with motor and sensory functions related to the lower limb. If this phenotype is shown to predict symptom development in longitudinal studies, it could be used as an early biomarker of AD

    Exploring computerised cognitive training as a therapeutic intervention for people with Huntington's disease (CogTrainHD): protocol for a randomised feasibility study

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    Background Cognitive impairments, especially deficits of executive function, have been well documented as a core and early feature in Huntington’s disease (HD). Cognitive impairments represent considerable burden and can be devastating for people and families affected by HD. Computerised cognitive training interventions that focus on improving executive function present a possible non-pharmacological treatment option. We propose to determine the feasibility, acceptability, and appropriate outcome measures for use in a randomised controlled feasibility study. Methods/design Participants will be randomised into either a computerised cognitive training group or a control group. Those randomised to the training group will be asked to complete a cognitive training intervention based on the HappyNeuron Pro software tasks of executive function, for a minimum of 30 min, three times a week for the 12-week study duration. Participants in the control group will not receive computerised cognitive training but will receive a similar degree of social interaction via equivalent study and home visits. We will explore quantitative outcome measures, including measures of cognitive performance, motor function, questionnaires and semi-structured interviews, as well as magnetic resonance imaging (MRI) measures in a subset of participants. Feasibility will be determined through assessment of recruitment, retention, adherence and acceptability of the intervention. Discussion The results of this study will provide crucial guidance and information regarding the feasibility of conducting a randomised controlled study into computerised cognitive training in HD. This study is crucial for the development of larger definitive randomised controlled trials which are powered to determine efficacy and for the development of future cognitive training programmes for people affected by HD

    A randomised feasibility study of computerised cognitive training as a therapeutic intervention for people with Huntington's disease (CogTrainHD)

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    Background Huntington’s disease (HD) is associated with a range of cognitive deficits including problems with executive function. In the absence of a disease modifying treatment, cognitive training has been proposed as a means of slowing cognitive decline; however, the impact of cognitive training in HD patient populations remains unclear. The CogTrainHD study assessed the feasibility and acceptability of home-based computerised executive function training, for people impacted by HD. Methods Thirty HD gene carriers were recruited and randomised to either executive function training or non-intervention control groups. Participants allocated to the intervention group were asked to complete executive function training three times a week for 30 min for 12 weeks in their own homes. Semi-structured interviews were conducted with participants and friends, family or carers, to determine their views on the study. Results 26 out of 30 participants completed the baseline assessments and were subsequently randomised: 13 to the control group and 13 to the intervention group. 23 of the 30 participants were retained until study completion: 10/13 in the intervention group and 13/13 in the control group. 4/10 participants fully adhered to the executive function training. All participants in the control group 13/13 completed the study as intended. Interview data suggested several key facilitators including participant determination, motivation, incorporation of the intervention into routine and support from friends and family members. Practical limitations, including lack of time, difficulty and frustration in completing the intervention, were identified as barriers to study completion. Conclusions The CogTrainHD feasibility study provides important evidence regarding the feasibility and acceptability of a home-based cognitive training intervention for people with HD. Variable adherence to the cognitive training implies that the intervention is not feasible to all participants in its current form. The study has highlighted important aspects in relation to both the study and intervention design that require consideration, and these include the design of games in the executive function training software, logistical considerations such as lack of time, the limited time participants had to complete the intervention and the number of study visits required. Further studies are necessary before computerised executive function training can be recommended routinely for people with HD

    L'influence des actions corporelles sur la perception et le comportement social : Ă©valuation des effets des postures de pouvoir

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    Expansive and constrictive body postures serve a primary communicative function in humans and other animals by signalling power and dominance. Whether adopting such “power postures” influences the agent’s own perception and behaviour is currently a subject of debate. In this PhD thesis, I explored effects of adopting power postures on behaviours closely related to the postures’ primary function of social signalling by focusing on responses to faces as particularly salient social signals. In a series of experiments, I utilized reverse correlation methods to visualize mental representations of preferred facial traits. Mental representations of implicitly as well as explicitly preferred faces evoked an affiliative and slightly dominant impression, but revealed no replicable effects of power postures. Two further separate experiments investigated posture effects on the perception of threatening facial expressions, and approach vs. avoidance actions in response to such social signals. While postures did not influence explicit recognition of threatening facial expressions, they affected approach and avoidance actions in response to them. Specifically, adopting a constrictive posture increased the tendency to avoid individuals expressing anger. Finally, an attempt to replicate posture effects on levels of testosterone and cortisol demonstrated that even repeatedly adopting a power posture in a social context does not elicit hormonal changes. Altogether, these findings suggest that our body posture does not influence our mental representations and perception of other people’s faces per se, but could influence our actions in response to social signals.Les postures corporelles signalant domination ou soumission servent une fonction de communication chez les humains et d’autres animaux. La question de savoir si l'adoption de telles "postures de pouvoir" influence la perception et le comportement de l'agent fait actuellement l'objet d'un dĂ©bat. Le travail rĂ©alisĂ© pendant cette thĂšse consistait Ă  explorer les effets de ces postures sur des comportements Ă©troitement liĂ©s Ă  leur fonction primaire, Ă  savoir la communication sociale, en se focalisant sur les rĂ©ponses aux visages, signaux sociaux particuliĂšrement saillants. Dans une sĂ©rie d'expĂ©riences, j'ai utilisĂ© des mĂ©thodes de corrĂ©lation inverse pour visualiser les reprĂ©sentations mentales de traits prĂ©fĂ©rĂ©s du visage. Les reprĂ©sentations mentales des visages prĂ©fĂ©rĂ©s implicitement et explicitement Ă©voquaient une impression affiliative et lĂ©gĂšrement dominante, mais ne rĂ©vĂ©laient aucun effet reproductible des postures. Deux autres expĂ©riences distinctes ont Ă©tudiĂ© les effets de la posture sur la perception d’expressions faciales menaçantes et sur les comportements d'approche ou d'Ă©vitement en rĂ©ponse Ă  ces signaux. Bien que les postures n'aient pas d’influence sur la reconnaissance explicite d’expressions faciales menaçantes, elles ont un impact sur les dĂ©cisions d'approcher ou d'Ă©viter des signaux de menace. Plus prĂ©cisĂ©ment, l'adoption d'une posture de soumission augmentait la tendance Ă  Ă©viter les personnes exprimant la colĂšre. Enfin, une tentative de rĂ©plication des effets des postures sur les niveaux de testostĂ©rone et de cortisol a dĂ©montrĂ© que mĂȘme l'adoption rĂ©pĂ©tĂ©e d'une posture de pouvoir en contexte social ne provoque pas de changements hormonaux. Dans l'ensemble, ces rĂ©sultats suggĂšrent que notre posture corporelle n’influence pas nos reprĂ©sentations mentales et notre perception des autres individus, mais pourrait influencer nos actions en rĂ©ponse aux signaux sociaux

    An album of protest: assembling narratives from the Hambacher Forst squat

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    An Album of protest: The assemblage of narratives derived from the squat occupying the Hambacher Forst tells stories of the life within a squatted forest in Germany. The album illustrates a collection of various individual perspectives presented via artworks including paintings, photographs and poems; as well as by gaining insights in the process of transformative learning and the ‘decolonisation of the mind’ of individuals and the collective expressed in notes and interviews of and with the activists. The Hambacher Forst community empowers its members. The profoundness of this impact on the activist’s biographies is unpredictable at this stage. The data gathered in the forest is incorporated and analysed according to existing literature in the fields of political ecology, protest culture and theory about the biographical impact of activism, social movement learning and transformative learning. Different forms of resistance as civil disobedience, temporary autonomous zones, violence/destruction, mummery and humour are portrayed in the paper. Moreover, the album elaborates the overvalued status of the concept of nature in ecology, its incoherence and its vulnerability of being misused for ideological justifications. People engaged in social movements require a critical examination of political ethics and philosophies. Further research about activist’s concepts and philosophies of nature are of interest. The methodological approach applied in this research intends to be radical and aims for creating a temporary autonomous zone to challenge the dominant hegemony of academic writing. The dissertation is submitted as a Prezi Presentation to allow the exploration via a multiplicity of pathways

    Social drivers and algorithmic mechanisms on digital media

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    On digital media, algorithms that process data and recommend content have become ubiquitous. Their fast and barely-regulated adoption has raised concerns about their role in well-being both at the individual and collective levels. Algorithmic mechanisms on digital media are powered by social drivers, creating a feedback loop that complicates research to disentangle the role of algorithms and already existing social phenomena. Our brief overview of the current evidence on how algorithms affect well-being, misinformation, and polarization suggests that the role of algorithms in these phenomena is far from straightforward and that substantial further empirical research is needed. Existing evidence suggests that algorithms mostly reinforce existing social drivers, which stresses the importance of reflecting on algorithms in the larger societal context including individualism, populist politics, and climate change. We present concrete ideas and research questions to improve algorithms on digital platforms and to investigate their role in current problems and potential solutions. Finally, we discuss how the current shift from social media to more algorithmically-curated media brings both risks and opportunities if algorithms are designed for individual and societal flourishing rather than short-term profit
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