Subjective Representation Research Articles

Queerying the Queensland senior English prescribed text list

AbstractThis paper presents an analysis of the prescribed text list for senior school English (including English as an Additional Language or Dialect, EAL/D) in Queensland, Australia. Queer understandings about the normalization of cisgender and heterosexuality provide a framework to analyze prescribed texts for adolescent learners. Hetero‐cisgender norms are perpetuated through overrepresentation in endorsed texts. Representations of queer subjectivities or themes in the most highly promoted texts, those appearing on the examination list, are infrequent and minor. Reflexive justice thinking acknowledges the critique of merely identifying “who is missing” in the literature and extends the discussion to consider the complexities of the social, cultural, and political contexts that influence who gets to decide.

Bibliometric analysis of technology readiness and education in high-impact journals of social sciences

In this bibliometric study, the close relationship between technology readiness and education is explored, particularly within the realm of social sciences. The main objective is to identify global trends and behaviors associated with these concepts. A qualitative scientometric review methodology was employed, focusing on the Web of Science (WoS) database, with 1366 articles analyzed. The application of various laws revealed the fundamental importance of Technology Readiness and Education for the long-term success of organizations in the digital age. Investing in the development of Technology skills strengthens competitiveness and fosters innovation. However, a minimal representation of educational topics in Social Sciences was observed, accounting for only 0.03% of the total articles. This knowledge gap is crucial to address, as training in technology and education is essential for both professional and scientific success. Having the appropriate competencies in technology and education is imperative to achieve greater productivity and professional success across various domains.

Echoes of Culture: Relationships of Implicit and Explicit Attitudes With Contemporary English, Historical English, and 53 Non-English Languages

Attitudes are intertwined with culture and language. But to what extent? Emerging perspectives in attitude research suggest that cultural representations in language are more related to implicitly measured (vs. explicitly measured) attitudes, and that such relationships persist across history and diverse languages. We offer a comprehensive test of these ideas by correlating (a) attitudes toward 55 topics (e.g., Rich/Poor, Dogs/Cats, Love/Money) from ~100,000 U.S. English-speaking participants with (b) representations of those same topics in word embeddings from contemporary English text, 200 years of English books, and 53 non-English languages. Strong and robust relationships emerged between representations in contemporary English and implicitly but not explicitly measured attitudes. Moreover, strong correlations with implicitly measured attitudes persisted across 200 years of books, and most non-English languages. Results provide new insights into the nature of implicitly measured attitudes and how they are intertwined with cultural representations that are relatively hidden in patterns of language across time and place.

Semi-supervised topic representation through sentiment analysis and semantic networks

This paper proposes a novel approach to topic detection aimed at improving the semi-supervised clustering of customer reviews in the context of customers' services. The proposed methodology, named SeMi-supervised clustering for Assessment of Reviews using Topic and Sentiment (SMARTS) for Topic-Community Representation with Semantic Networks, combines semantic and sentiment analysis of words to derive topics related to positive and negative reviews of specific services. To achieve this, a semantic network of words is constructed based on word embedding semantic similarity to identify relationships between words used in the reviews. The resulting network is then used to derive the topics present in users' reviews, which are grouped by positive and negative sentiment based on words related to specific services. Clusters of words, obtained from the network's communities, are used to extract topics related to particular services and to improve the interpretation of users' assessments of those services. The proposed methodology is applied to tourism review data from Booking.com, and the results demonstrate the efficacy of the approach in enhancing the interpretability of the topics obtained by semi-supervised clustering. The methodology has the potential to provide valuable insights into the sentiment of customers toward tourism services, which could be utilized by service providers and decision-makers to enhance the quality of their services.

РЕПРЕЗЕНТАЦИЯ ПОСТЧЕЛОВЕЧЕСКОЙ СУБЪЕКТИВНОСТИ В СОВРЕМЕННОЙ ФАНТАСТИКЕ НА ПРИМЕРЕ СЕРИАЛА «ЛЮБОВЬ. СМЕРТЬ. РОБОТЫ»

Today, the conversation about the impact of technology on humans is a common place. In humanitarian theory, there is a growing number of approaches that develop new ways to describe a person in a technologized culture. Special attention is paid to it by posthumanism, based on the experience of critical analysis of culture, it offers a description of alternative, posthuman subjectivity. Where is also a reflection on changing human relations with the environment in visual art. Although mass screen culture has transformed and moved away from big screens to gadgets for private viewing, it has not lost its ability to respond sensitively to cultural trends and offers examples of images of posthuman subjectivity. The theory of posthumanism turns out to be a relevant tool for analyzing posthuman images in modern science fiction films. The article will examine representations of posthuman subjectivity in the genre of modern fiction on the example of the TV series “Love. Death. Robots.” The focus of the analysis will be on the images of the main characters and the peculiarities of plot development in relation to traditional cultural constructs.

Illness perception in functional neurological disorder: low illness coherence and personal control

IntroductionIllness perception refers to patients’ subjective representations and appraisals of somatic and mental symptoms. These are relevant for self-management and outcome. In clinical practice, patients with functional neurological disorder (FND)...

Weighing the gold standard: The breadth of emergency medicine core content covered by textbooks.

Textbooks are often considered the criterion standard in medical education, but there is a growing preference for free open-access medical education (FOAM) content among learners. Despite FOAM's appeal, these resources often fall short in covering core content as comprehensively as the American Board of Emergency Medicine's 2019 Model of the Clinical Practice of Emergency Medicine (MCPEM), thereby sustaining the recommendation for textbook use. However, textbooks have limitations, such as how quickly content can become outdated. Notably, there is no evaluation of the comprehensiveness of emergency medicine (EM) textbooks in the literature. This observational cross-sectional study compared Rosen's Emergency Medicine: Concepts and Clinical Practice 10th Edition (Rosen's) and Tintinalli's Emergency Medicine: A Comprehensive Study Guide 9th Edition (Tintinalli's) with the MCPEM subtopics. Each textbook chapter was reviewed for content alignment with MCPEM subtopics. The primary outcome was the proportion of MCPEM subtopics covered by each textbook. Secondary outcomes included the count of chapters covering each topic and their distribution relative to the core content weighting in the ABEM National Qualifying Examination (NQE). Rosen's covered 95.3% of MCPEM subtopics (837 unique subtopics), and Tintinalli's covered 94.5% (826 unique subtopics). Both textbooks overrepresented topics like toxicology and psychobehavioral disorders compared to their weighting in the NQE. Relatively underrepresented topics included environmental disorders, cardiovascular disorders, renal and urogenital disorders, and traumatic disorders in Rosen's and other core competencies and cardiovascular disorders in Tintinalli's. The textbooks varied significantly in coverage of certain topics. Both Rosen's and Tintinalli's comprehensively cover MCPEM subtopics, with some discrepancies in topic representation compared to the NQE. While textbooks offer depth and breadth, they may not fully align with the NQE content distribution. A diversified approach to EM education, combining traditional textbooks and FOAM resources may be required for comprehensive learning.

Comments on energy conservation treatments for MS-related fatigue and a new proposal

Psychological treatments of MS-related fatigue mostly depend on energy conservation programs. We argue that the evidence for energy conservation training is weak – in contrast to some reviews on this topic. The reasons for our concerns are the use of informed passive control groups allowing negative placebo effects, the lack of predefined primary outcome parameter, statistically rather than clinically significant effects, and the use of insensitive fatigue questionnaires. We propose to base psychological interventions not on a view of fatigue as a constant loss of mental energy but as a subjective representation (“feeling”) of an inflammatory state, which draws away attentional capacity. This conceptualization allows to develop a three-step treatment approach: Getting short-term control on fatigue, extinction to reduce fatigue-related avoidance behavior, and a systematic increase of activities by pacing. Our proposal depends on the techniques, that can interrupt ongoing feelings of fatigue and can serve as a basis for extinction. We propose that Progressive Muscle Relaxation might be such a technique. The advantage of our model is that it shares similarities with well-established treatments for phobias and chronic pain and we discuss the shared set of assumptions. Hopefully, this will help to improve the treatment of fatigue in future.

Aligning Human and Computational Coherence Evaluations

Abstract Automated coherence metrics constitute an efficient and popular way to evaluate topic models. Previous works present a mixed picture of their presumed correlation with human judgment. This work proposes a novel sampling approach to mine topic representations at a large-scale while seeking to mitigate bias from sampling, enabling the investigation of widely-used automated coherence metrics via large corpora. Additionally, this article proposes a novel user study design, an amalgamation of different proxy tasks, to derive a finer insight into the human decision-making processes. This design subsumes the purpose of simple rating and outlier-detection user studies. Similar to the sampling approach, the user study conducted is very extensive, comprising forty study participants split into eight different study groups tasked with evaluating their respective set of one hundred topic representations. Usually, when substantiating the use of these metrics, human responses are treated as the golden standard. This article further investigates the reliability of human judgment by flipping the comparison and conducting a novel extended analysis of human response at the group and individual level against a generic corpus. The investigation results show a moderate to good correlation between these metrics and human judgment, especially for generic corpora, and derive further insights into the human perception of coherence. Analysing inter-metric correlations across corpora shows moderate to good correlation amongst these metrics. As these metrics depend on corpus statistics, this article further investigates the topical differences between corpora revealing nuances in applications of these metrics.

Making Sense of Dementia: Older Adults' Subjective Representations of Dementia and Alzheimer's Disease.

This research explores how the representations and meanings of living with dementia are constructed by older adults. Focus groups (N = 19) and in-depth interviews (N = 29) were conducted with older adults aged 65+ living in the Czech Republic, representing different levels of personal familiarity with care for an individual experiencing dementia. We identified 2 different discourses: (1) Tragedy discourse with two distinctive repertoires "dementia as a thief of personality" and "dementia as a thief of humanity." Within such discourse, dementia transcends mere medical terminology, serving as a symbolic representation of existential anxieties linked to aging and the perceived loss of control. (2) The discourse of Dementia as a specific way in which people approach the world was articulated mainly by caregivers, providing them with a coping mechanism and a means to reconstruct the agency of the person experiencing dementia. In older adults' representations, references to suffering among family members emerged as a primary association with dementia. Dementia was portrayed as "contagious" in its effect on the family members who were, in a sense, depicted as the primary sufferers of the disease. Dementia often serves as a symbolic tool for older adults to articulate concerns about advanced old age, extending beyond its clinical definition to convey deep-seated fears associated with aging. The experience of people surrounding those diagnosed with dementia and the permeability of the impacts of this disease between bodies represented crucial frameworks for conceptualizing dementia in the narratives of older adults.

Supersymmetric domain walls in maximal 6D gauged supergravity III

We continue our study of gaugings the maximal N=(2,2)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$N=(2,2)$$\\end{document} supergravity in six dimensions with gauge groups obtained from decomposing the embedding tensor under R+×SO(4,4)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathbb {R}}^+\ imes SO(4,4)$$\\end{document} subgroup of the global symmetry SO(5, 5). Supersymmetry requires the embedding tensor to transform in 144c\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ extbf{144}}_c$$\\end{document} representation of SO(5, 5). Under R+×SO(4,4)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathbb {R}}^+\ imes SO(4,4)$$\\end{document} subgroup, this leads to the embedding tensor in (8±3,\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$({\ extbf{8}}^{\\pm 3},$$\\end{document}8±1,56±1)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ extbf{8}}^{\\pm 1},{\ extbf{56}}^{\\pm 1})$$\\end{document} representations. Gaugings in 8±3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ extbf{8}}^{\\pm 3}$$\\end{document} representations lead to a translational gauge group R8\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathbb {R}}^8$$\\end{document} while gaugings in 8±1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ extbf{8}}^{\\pm 1}$$\\end{document} representations give rise to gauge groups related to the scaling symmetry R+.\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathbb {R}}^+.$$\\end{document} On the other hand, the embedding tensor in 56±1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ extbf{56}}^{\\pm 1}$$\\end{document} representations gives CSO(4-p,p,1)∼SO(4-p,p)⋉R4⊂SO(4,4)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$CSO(4-p,p,1)\\sim SO(4-p,p) < imes {\\mathbb {R}}^4\\subset SO(4,4)$$\\end{document} gauge groups with p=0,1,2.\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p=0,1,2.$$\\end{document} More interesting gauge groups can be obtained by turning on more than one representation of the embedding tensor subject to the quadratic constraints. In particular, we consider gaugings in both 56-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ extbf{56}}^{-1}$$\\end{document} and 8+3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ extbf{8}}^{+3}$$\\end{document} representations giving rise to larger SO(5-p,p)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SO(5-p,p)$$\\end{document} and SO(4-p,p+1)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SO(4-p,p+1)$$\\end{document} gauge groups for p=0,1,2.\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p=0,1,2.$$\\end{document} In this case, we also give a number of half-supersymmetric domain wall solutions preserving different residual symmetries. The solutions for gaugings obtained only from 56-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ extbf{56}}^{-1}$$\\end{document} representation are also included in these results when the 8+3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ extbf{8}}^{+3}$$\\end{document} part is accordingly turned off.

Enhancing user sequence representation with cross-view collaborative learning for depression detection on Sina Weibo

Detecting depression through social media is a crucial task in the era of mobile media. Several methods have been proposed for modeling user behavior sequences among social media users with depression. However, existing methods often overlook the dynamic dependencies between user behaviors. Moreover, previous research has overlooked the importance of incorporating multi-perspective information in personalized user modeling. Therefore, we propose a cross-view collaborative learning method for user behavior sequence modeling. Specifically, we built a post-level behavior graph for each individual and employed a graph neural network (GNN) to model the contextual dependencies between user behaviors. We propose using Long Short-Term Memory (LSTM) networks to capture the sequential evolution of user behavior. Additionally, we introduce a node-level attention mechanism to aggregate node representations and obtain graph-level semantic representations. Next, we leverage a BERTopic-based model to extract personalized topics and interesting knowledge from each individual’s posts. These knowledge elements are then aggregated to form user-level topic representations. We propose a cross-view collaborative learning method to integrate temporal behavior and topic semantic representations dynamically. This method effectively addresses the semantic alignment and fusion issues across views and enhance the ability of our model to detect depression. Finally, to evaluate the proposed model, we constructed a well-annotated Chinese dataset based on Sina Weibo for user-level depression behavioral modeling. Extensive experimental results and analyses on both datasets demonstrated the effectiveness and advancement of our model for user-level depression detection task.

“Come to life” realism: View‐Master reels and the legacy of stereoscopic imperialism

AbstractI argue that View‐Master reels upheld the colonial legacy of previous stereoscopic depictions of Indigenous subjects while inaugurating new methods of asserting power in exhibition via its ease of use and “black‐box” structure. Further, focusing on the instrumentalization of stereoscopy allows us to think through how these images intervene in the history of the representation of Indigenous subjects across image media and histories of photographic technology and consumption. In sum, although stereoscopy functions as a marketable tool for narrativizing colonial power, its affective qualities and historical contexts complicate fantasies of unilateral viewing and domination and bring forth histories of resistance.

Narratives from GPT-derived networks of news and a link to financial markets dislocations

AbstractWe introduce a novel framework to study the dynamics of news narratives, by leveraging GPT3.5 advanced text analysis capabilities and graph theory. In particular, we focus on a corpus of economic articles from The Wall Street Journal and dynamically extract the main topics of discussion over time, in a completely systematic and scalable fashion. As a simple application of the suggested approach, we show how the structure of such topics of discussion has a statistically significant relationship with the contemporaneous state of financial markets, which can be used to construct an investment strategy or monitor financial risks. Our work is based on the intrinsic ability of GPT models to track the context of sentences within a document, thanks to which we can accurately extract a ranking of the most important entities discussed within each article, and evaluate their entity-specific sentiments. Then, we create a graph for each week of data, in which nodes are the entities retrieved and edges are built from the co-occurrence of such entities within articles. Graph centrality measures are computed over time to track the most representative keywords of topics of discussion, which result in an accurate summary view of the evolution of economic narratives. Fuzzy community detection is finally used to cluster linked entities into a more detailed representation of topics. Such groups of entities are mapped to the related journal articles, which are in turn summarised to reach a highly nuanced and interpretable view of the topics discussed within each week. Linking the features of these topics to the relevant financial market time series, we find that high fragmentation within our networks’ communities relates to moments of financial markets dislocations (i.e. dates with unusually high volatility across asset classes). This result should thus motivate stronger effort within financial research to move beyond ubiquitous sentiment analysis of news and delve deeper into broader and more holistic studies of textual data.

Ukraine in Popular Culture: Editorial for a Special Issue

This special issue explores how popular culture shapes local, regional, national, and global perceptions of Ukraine amid the ongoing war with Russia. Integrating literatures on popular geopolitics, vernacular and aesthetic IR, and Ukraine studies, we delve into the complexities of the knowledge-making about Ukraine that takes place at the interstices of the everyday, the aesthetic, and the international. Given the mutually implicated relationship between popular culture and world politics, the popular representations of the Ukrainian subject both mirror and shape prevailing narratives, practices, identities, and power relations. But we also inquire into how popular culture serves as a space for political resistance and activism by those existing at the margins of world politics. By centering the Ukrainian perspective in all its multiplicity, the special issue helps to challenge the Western- and Russian-centric prism through which Ukraine has been approached in IR and related disciplines.

Personalized anti-tumor drug efficacy prediction based on clinical data

Anti-tumor drug efficacy prediction poses an unprecedented challenge to realizing personalized medicine. This paper proposes to predict personalized anti-tumor drug efficacy based on clinical data. Specifically, we encode the clinical text as numeric vectors featured with hidden topics for patients using Latent Dirichlet Allocation model. Then, to classify patients into two classes, responsive or non-responsive to a drug, drug efficacy predictors are established by machine learning based on the Latent Dirichlet Allocation topic representation. To evaluate the proposed method, we collected and collated clinical records of lung and bowel cancer patients treated with platinum. Experimental results on the data sets show the efficacy and effectiveness of the proposed method, suggesting the potential value of clinical data in cancer precision medicine. We hope that it will promote the research of drug efficacy prediction based on clinical data.

When Science Meets Art on Instagram: Examining the Effects of Visual Art on Emotions, Interest, and Social Media Engagement

While artistic representations of scientific subjects, phenomena, and data have gained traction on social media, their effects on audience engagement remain understudied. Using an experiment with Instagram users in the United States ( N = 655), this study found that exposure to artistic representations of COVID-19 information on Instagram significantly increased individuals’ interest and positive emotions compared with exposure to informationally equivalent data graphs. Positive emotions also mediated the relationship of art exposure on one’s liking and sharing of Instagram posts. We discuss the potential roles of visual art and social media in shaping public engagement with science.

Public Opinion Evolution in Cyberspace: A Case Analysis of Pelosi’s Visit to Taiwan

The dynamics of public opinion on social media affects people’s feeling and minds about international affairs and leads to the reconstruction of societal states for international conflicts. In this article, we analyze the topics’ evolution on social media during the Pelosi visit. Such kind of analysis should help the related departments sense and beware the situation effectively and efficiently, and may provide technical supports for proper policy making and responses. To facilitate this purpose, a new method is proposed and an abbreviated large-graph clustering (ALGC) algorithm has been designed to generate documents and topic representation for alleviating the overhead of high computational complexity of large graphs by reducing the dimensionality of the attention matrix and adjacency matrix. The evolution pattern of topics is also analyzed in and between different time periods. Experiment results show that the proposed method performs well, achieving a high clustering accuracy with lower computational cost. The dataset used in this article is also released for public analysis.

A Medical Education Research Library: key research topics and associated experts

ABSTRACT When clinician-educators and medical education researchers use and discuss medical education research, they can advance innovation in medical education as well as improve its quality. To facilitate the use and discussions of medical education research, we created a prefatory visual representation of key medical education research topics and associated experts. We conducted one-on-one virtual interviews with medical education journal editorial board members to identify what they perceived as key medical education research topics as well as who they associated, as experts, with each of the identified topics. We used content analysis to create categories representing key topics and noted occurrences of named experts. Twenty-one editorial board members, representing nine of the top medical education journals, participated. From the data we created a figure entitled, Medical Education Research Library. The library includes 13 research topics, with assessment as the most prevalent. It also notes recognized experts, including van der Vleuten, ten Cate, and Norman. The key medical education research topics identified and included in the library align with what others have identified as trends in the literature. Selected topics, including workplace-based learning, equity, diversity, and inclusion, physician wellbeing and burnout, and social accountability, are emerging. Once transformed into an open educational resource, clinician-educators and medical education researchers can use and contribute to the functional library. Such continuous expansion will generate better awareness and recognition of diverse perspectives. The functional library will help to innovate and improve the quality of medical education through evidence-informed practices and scholarship.

The problematic space between art, ambition, and gameplay: The Medium and the issues concerning difficult subject matter and gameplay in games

This article identifies and examines a couple of selected issues regarding speculative digital games which endeavor to deal with serious subject matter. Due to the fact that speculative games are exceptionally well suited for symbolic representation of sensitive topics, they allow their creators to conceive ambitious projects that aspire to be great works of audiovisual art. However, because game texts belong to a very specific medium, it is not always possible to realize this ambition in the context of gameplay. For reasons of space and focus this article uses one particular game, The Medium (2021), to serve as the primary example of how the problems which occur in the process of combining specific, engaging gameplay with serious, sensitive subject matter, lead to situations in which a game can fail to fulfill the player’s expectations. By analyzing the structure, gameplay, and storytelling tools employed in The Medium, the article places emphasis on the significance of the possible tensions between the intention of the designers of the game experience and the experiences, ideas, and interpretations the players themselves bring to the game text.