Communication Research Research Articles

Multilingualism in Scientific Literature Communicated by Journals from the SciELO Brazil Collection

This article describes the internationalization of the Scientific Electronic Library Online (SciELO), an open-science programme aimed at the development of capacities and infrastructure in research communication. It manages open-access collections of preprints, articles, research data, books, and book chapters, with a focus on national collections of non-profit peer-reviewed journals published by research communities of academic institutions, scientific societies, and associations. Celebrating 25 years of regular operation, SciELO improves research communication through professionalization, internationalization and sustainability of the indexed journals, maximizing their visibility and impact. In Brazil, the internationalization efforts by SciELO are aligned with national research policies, especially the internationalization of graduate programmes. The SciELO Brazil collection of journals evolves by adopting English solely or with Portuguese to improve the contribution of multilingualism to performing research by subject field. This article covers two decades of scientific literature in SciELO Brazil from 2003 to 2022. During this time, articles written in English or simultaneously in Portuguese and English increased significantly, resulting in a corresponding rise in access and citations received. The progress of the internationalization of the journals in the SciELO Brazil collection through multilingualism has been challenging both operationally and programmatically.

A Self-Supervised GCN Model for Link Scheduling in Downlink NOMA Networks

INTRODUCTION: Downlink Non-Orthogonal Multiple Access (NOMA) networks pose challenges in optimizing power allocation efficiency due to their complex design.OBJECTIVES: This paper aims to propose a novel scheme utilizing Graph Neural Networks to address the optimization challenges in downlink NOMA networks.METHODS: We transform the optimization problem into an optimal link scheduling problem by modeling the network as a bipartite graph. Leveraging Graph Convolutional Networks, we employ self-supervised learning to learn the optimal link scheduling strategy.RESULTS: Simulation results showcase a significant enhancement in power allocation efficiency in downlink NOMA networks, evidenced by notable improvements in both average accuracy and generalization ability. CONCLUSION: Our proposed scheme demonstrates promising potential in substantially augmenting power allocation efficiency within downlink NOMA networks, offering a promising avenue for further research and application in wireless communications.

Counter-Mapping in Geographic Education: A Novel Approach to Understanding Urban and Cultural Dynamics in Cities

This study assessed the impact of counter-mapping on university students’ perception and knowledge of their cities, focusing on cultural diversity, urban dynamics, and social challenges. Using a quasi-experimental design with pretests and posttests in the province of Alicante, Spain, changes in the understanding of urban geography, everyday life, and cultural diversity were analyzed among 54 Geography Didactics students. Likert scale surveys and open-ended questions were employed, complemented by statistical and qualitative analyses, to measure knowledge and perceptions before and after the counter-mapping project. The results indicate that although quantitative correlations did not show statistically significant significance, qualitative analysis revealed significant and profound learning. Participants uncovered the hidden layers of their urban environments and gained a better understanding of the complexities and challenges of their cities. The project promoted the development of critical skills such as analytical thinking, active research, and effective communication, proving to be a valuable pedagogical tool that surpasses the limitations of traditional teaching methods and encourages active and committed citizenship. This inclusive and multidimensional approach enriches the diversity of experiences and knowledge, significantly contributing to the teaching of urban subjects, community engagement, and social responsibility and laying the groundwork for the proper tourist, cultural, social, or urban planning of city spaces.

How CEOs can Increase Public Engagement via Microblogs: The Role of CEO Gender and Content Orientation

AbstractIn the social media era, Chief Executive Officers (CEOs) are increasingly using microblogging sites to communicate with the public. Drawing on schema‐congruity theory and gender egalitarianism, we investigate how CEO gender and work–life content orientation interact to influence public engagement with CEOs on microblogs. Using China as our research setting, we conduct a content analysis of data collected from 63 high‐profile CEOs’ microblogs and four laboratory studies with some 2000 respondents. Our results show that for female CEOs, work‐related content leads to greater engagement than life‐related content; for male CEOs, the effect is reversed. We find that such outcomes are driven by the incongruity between stereotypical gender roles and content orientation, which enhances perceived novelty and audience interest, thus leading to greater engagement. This effect diminishes when the audience has a very high or very low perception of gender equality in their society; or when the audience supports male privilege values personally. Our research provides new theoretical insights for online leadership communication, public engagement and gender research. It also offers useful managerial guidance for executives to effectively leverage the capabilities of social media in engaging with the public.

Administrative Communication Research in Radio and Film Studies: Reviewing the Audience Concept

In the early 20th century, during the nascent stages of communication research, the focal point revolved around the intricate interplay between the public sphere, democracy, and the emergence of public opinion. The profound influence of mass media on audiences took center stage in scholarly inquiries. Notably, pivotal milestones in radio and film studies marked the genesis of this field, fundamentally shaping our understanding of listeners and viewers. As the discipline evolved, radio research paved the way for extensive viewer studies within the realm of television research. Concurrently, viewer studies in the context of cinema began to assert their autonomy, gradually establishing a distinct identity. While both mediums received substantial support from foundations, film studies gradually diverged from the overarching umbrella of mass communication studies, solidifying its place as an independent academic field. Conversely, radio studies persist within the framework of mass communication research, akin to another facet of television research. This article delves into the nuances of this transformative journey, scrutinizing the shifting landscapes of administrative efforts buoyed by foundations. It probes into the alterations in the orientations of viewer studies and contemplates potential transformations in the conceptualization of audiences in the digital age. The narrative builds upon themes and potential conceptualizations, offering a comprehensive exploration of audience studies, film studies, and radio studies within the dynamic tapestry of administrative communication.

Methods Showcase—Using PLSF-SEM in Business Communication Research

Structural equation modeling (SEM) is a data analysis method that is widely used in business communication research, as well as research in many other fields, when scholars need to test complex models with multiple outcomes, interactions, or operations across different situations. To date, however, researchers have had to choose between using covariance-based SEM, and dealing with convergence problems; or composite-based SEM, and facing serious methodological issues. This article describes a way to combine strong aspects of both SEM types through PLSF-SEM. By utilizing this novel method, empirical researchers can employ several of the same tests traditionally used in covariance-based SEM, as well as new tests that rely on latent variable estimates, in a succinct and scholarly way. PLSF-SEM builds on partial least squares (PLS) algorithms to generate correlation-preserving factors; the F refers to it being factor-based, as opposed to composite-based. A primer on the use of PLSF-SEM in business communication research is provided, based on an illustrative model inspired by motivating language theory, and where simulated data was analyzed with the software WarpPLS.

Using incident reports to diagnose communication challenges for precision intervention in learning health systems: A methods paper.

Poor communication is a leading root cause of preventable maternal mortality in the United States. Communication challenges are compounded with the presence of biases, including racism. Hospital administrators and clinicians are often aware that communication is a problem, but understanding where to intervene can be difficult to determine. While clinical leadership routinely reviews incident reports and acts on them to improve care, we hypothesized that reviewing incident reports in a systematic way might reveal thematic patterns, providing targeted opportunities to improve communication in direct interaction with patients and within the healthcare team itself. We abstracted incident reports from the Women's Health service and linked them with patient charts to join patient's race/ethnicity, birth outcome, and presence of maternal morbidity and mortality to the incident report. We conducted a qualitative content analysis of incident reports using an inductive and deductive approach to categorizing communication challenges. We then described the intersection of different types of communication challenges with patient race/ethnicity and morbidity outcomes. The use of incident reports to conduct research on communication was new for the health system. Conversations with health system-level stakeholders were important to determine the best way to manage data. We developed a thematic codebook based on prior research in healthcare communication. We found that we needed to add codes that were equity focused, as this was missing from the existing codebook. We also found that clinical and contextual expertise was necessary for conducting the analysis-requiring more resources to conduct coding than initially estimated. We shared our findings back with leadership iteratively during the work. Incident reports represent a promising source of health system data for rapid improvement to transform organizational practice around communication. There are barriers to conducting this work in a rapid manner, however, that require further iteration and innovation.

Communication and Deliberation for Environmental Governance

Environmental governance occurs through and is shaped by communication. We propose a typology of public communication, classifying it by directionality (one-way or two-way) and objective (informational or operational). We then review how communication types influence individuals’ cognitive frames, values, and environmental behaviors. Though one-way communication is common, its impact is often limited to influencing cognitive frames. Research on two-way informational communication demonstrates a greater ability to align cognitive frames and values among individuals, and research on two-way operational communication demonstrates the greatest impact on conceptual frames, values, and environmental behaviors. Factors that affect the impact of communication include the medium through which it occurs, trust, timing, and social-material context. Among these, our review considers new directions in public communication research that focus on the role of digital platforms, misinformation, and disinformation. We conclude by synthesizing research on deliberative communication, a case of communication among citizens guided by democratic ideals.

Propositional claim detection: a task and dataset for the classification of claims to truth

AbstractThis paper introduces Propositional Claim Detection (PCD), an NLP task for classifying claims to truth, and presents a publicly available dataset for it. PCD is applicable in practical scenarios, for instance, for the support of fact-checkers, as well as in many areas of communication research. By leveraging insights from philosophy and linguistics, PCD is a more systematic and transparent version of claim detection than previous approaches. This paper presents the theoretical background for PCD and discusses its advantages over alternative approaches to claim detection. Extensive experiments on models trained on the dataset are conducted and result in an $$\hbox {F}_{1}$$ F 1 -score of up to 0.91. Moreover, PCD’s generalization across domains is tested. Models trained on the dataset show stable performance for text from previously unseen domains such as different topical domains or writing styles. PCD is a basic task that finds application in various fields and can be integrated with many other computational tools.

Investigating the relationship between heat load and shade seeking behaviour in dairy buffaloes.

The study presented in this Research Communication aimed to investigate the relationship between physiological responses, body surface temperature and shade-seeking behaviour in Nili Ravi dairy buffaloes during summer months. We enrolled 60 buffaloes, and each animal was observed for three consecutive days starting before sunrise until they moved towards the shade structures. A repeated measures ANOVA was employed to assess the changes in physiological parameters and body surface temperature between the early morning and the occurrence of shade-seeking behaviour. The average temperature humidity index and heat load index during the behavioural monitoring period (0400 to 1200 h) were 81.3 ± 6.5 and 92.9 ± 17, respectively (mean ± sd). There was no significant difference in core body temperature between sunrise and the time of shade-seeking event. However, the buffaloes had a slightly higher respiration rate at the time of shade-seeking (19.2 vs. 22.4 breaths/min). In addition, body surface temperature, measured at the flank region, shoulder, base of the ear and forehead was significantly higher at the occurrence of shade-seeking behaviour compared to the early morning. On average, the buffaloes sought shade when the surface temperature was 2°C higher than the temperature recorded before sunrise. Overall, the current findings suggest that body surface temperature, rather than core body temperature was strongly associated with shade-seeking behaviour in dairy buffaloes. These findings could be useful in developing strategies to mitigate the effects of heat stress in dairy buffalo herds and thereby improve animal welfare.

Image types revisited. A texto-material approach for creating image types

In visual communication research there are already several methodological approaches for creating image types. These approaches work with creating typologies based on the representational features of visuals / image motifs, reducing the complexity of extensive visual material. However, we argue that in everyday visual communication, the meaning of images depends largely on the practices in which they are embedded and not on the motif. This paper’s aim is to propose a methodological design for an image type analysis that considers both the representational and the artifact-related component of images, following a texto-material understanding of images. We illustrate the procedure step by step through an empirical study that explores visuals in couple relationships in Switzerland. The method enables a qualitative analysis of a large number of visuals that combines a) the creation of image types and b) a dynamic approach to in-depth visual analysis. Image types resulting from this procedure are more heterogeneous in motifs compared to previous traditions of image type analysis but allow for considering both the visual and the material dimensions of visuals, e.g., practices in which images are embedded. The approach builds on existing methods and contributes to the advancements of methods within visual communication research.

Images, clusters and types – Making sense of (large) image corpora and related practices in and with digital media

In November 2021, the Visual Communication Division of the German Communication Association (DGPuK) celebrated its 20th anniversary at the University of Trier with a one-year pandemic delay. Marion G. Müller, Katharina Christ and Christof Barth organized an excellent conference to mark the occasion and to reflect on past and current trends, topics, and challenges in visual communication research. Resuming the thematic scope of the division’s first conference held in Hamburg in 2000, the conference focused on “The power of images – Images of power. On visual political communication in digital contexts.” While analyses of press photography in the tradition of political iconology were the main approaches twenty years ago, the program of the anniversary conference demonstrated diversified thematic foci and methodological approaches. The presentations examined a broad range of visual digital media and visual communication exerted by various actors ranging from the press to politicians to activists and citizens. Concurrently, we also saw a considerable diversity concerning methodological approaches and a rising influence of computational methods for analyzing the increasingly large numbers of images in digital media environments. With the panel “Image type / image cluster analysis as an approach to analyzing large numbers of images in online environments,” a discussion on diverse methodological approaches and their potentials and challenges among our members started. After the conference, we decided to open up our internal discussion and reach out to international colleagues working on similar questions. The long-term result is this Thematic Section on diverse methods for structuring image data corpora drawing on different traditions of visual analysis.

Genotypic insights to Panton-Valentine leukocidin positive methicillin-resistant Staphylococcus aureus isolated from cattle mastitis.

In this research communication we investigate the prevalence and antimicrobial susceptibility of S. aureus harboring virulent genes responsible for mastitis in cattle of Punjab, Pakistan. A total of 690 milk samples were collected from commercial dairy farms for analysis of the prevalence of subclinical and clinical mastitis and isolation of S. aureus. Virulence ability and methicillin resistance in S. aureus (MRSA) was determined by targeting the pvl (the gene for Panton-Valentine leukocidin) and mecA genes, respectively. A total of 175 S. aureus isolates exhibiting prevalence of pvl gene (6.28%) and mecA gene (22.28%) were determined. Antimicrobial susceptibility testing of pvl positive and negative MRSA against different classes of antibiotics revealed 100% resistance against β-lactams while 100% sensitivity towards tylosin and linezolid.

A Research of Subtitle Translation and International Communication of Chinese Cultural Documentary from the Perspective of Eco-Translatology

A Research of Subtitle Translation and International Communication of Chinese Cultural Documentary from the Perspective of Eco-Translatology

Metasurface-based wide-angle reflective metalens with consistently constant focusing efficiency

Terahertz (THz) communication technology has drawn a lot of attention due to advancements in global research and aspirations for 6G communication as well as the development of THz technology. It is desirable to have a reflective metalens that can gather light from many directions and focus it at a fixed place. We employed the diffractive neural network (DNN) to design a wide-angle metasurface-based reflective metalens in order to meet this technical need. This reflective metalens is capable of consistently and efficiently reflecting incident light from a wide angle of incidence and focusing it into one spot. The DNN is used to quantitatively optimize the phase distribution of the reflective metalens and the resonance phase modulation approach is adopted to develop the unit structure. Both simulation and experimentation in a 220 GHz environment were used to confirm the reflective metalens's functionality. Through increased wide-angle reflection and directional focusing homogeneity and efficiency, the suggested technology offers a practical means of addressing the problems associated with 6G communication.

Delay of Transmitted Data in the Remote Patient Monitoring System through AMQP and CoAP

Remote Patient Monitoring (RPM) is a healthcare solution that uses technology to monitor patients outside conventional healthcare settings. It is especially useful for people with chronic conditions or needing regular monitoring. One of the main reasons for the increase in the number of deaths each year is the increase in cardiovascular diseases, including hypertension. Online blood pressure monitoring offers many advantages but also potential challenges. This work reviews the key communication technologies and research challenges in the real-time transmission of measured blood pressure data. Delay in these systems is not tolerated as it involves human lives. To conduct the experimental studies, a prototype of an experimental intelligent system was created to study the delay and processor load of the RPI4 gateway. The measured blood pressure data is sent to the Things Board cloud using the AMQP and CoAP protocols. The experimental results are particularly useful for RPM system designers. The results of this research facilitate an informed decision on the choice of protocol that transmits the data from the gateway to the cloud in the process of designing remote patient monitoring systems.

Audio-as-Data Tools: Replicating Computational Data Processing

The rise of audio-as-data in social science research accentuates a fundamental challenge: establishing reproducible and reliable methodologies to guide this emerging area of study. In this study, we focus on the reproducibility of audio-as-data preparation methods in computational communication research and evaluate the accuracy of popular audio-as-data tools. We analyze automated transcription and computational phonology tools applied to 200 episodes of conservative talk shows hosted by Rush Limbaugh and Alex Jones. Our findings reveal that the tools we tested are highly accurate. However, despite different transcription and audio signal processing tools yield similar results, subtle yet significant variations could impact the findings’ reproducibility. Specifically, we find that discrepancies in automated transcriptions and auditory features such as pitch and intensity underscore the need for meticulous reproduction of data preparation procedures. These insights into the variability introduced by different tools stress the importance of detailed methodological reporting and consistent processing techniques to ensure the replicability of research outcomes. Our study contributes to the broader discourse on replicability and reproducibility by highlighting the nuances of audio data preparation and advocating for more transparent and standardized practices in this area.

Message-level Claims Require Message-level Data Analyses: Aligning Claims and Evidence in Communication Research

ABSTRACT Researchers often invoke individual-level correlations (correlations between properties of individuals) as a basis for message-level claims (claims about properties of messages). For example: “People who are more transported by a narrative message are generally also more persuaded by it; individuals’ transportation and persuasion scores are positively correlated. Therefore narratives that are more transporting will be more persuasive than narratives that are less transporting.” But that inference is mistaken. The reasoning mistake is not specific to that example, but rather is a common mistake in communication research. This article explains the reasoning mistake, identifies multiple examples of the mistake, and discusses implications of and remedies for this circumstance.

V2V Communication in Smart Traffic Systems: Current status, challenges and future perspectives

Implementing V2V communication in intelligent traffic systems has been a topic of growing interest due to its potential to improve road safety and traffic flow. However, the widespread adoption of V2V communication in intelligent traffic systems could be enhanced by various challenges, such as infrastructure cost, security, and interoperability. These challenges must be addressed to improve the potential benefits of V2V communication. The problem statement of this study is to examine the potential benefits and challenges of V2V communication in intelligent traffic systems and provide insights into the current state of the art in V2V communication research. The proposed approach is to conduct a literature review of recent research on V2V communication in intelligent traffic systems to identify the potential benefits and challenges of V2V communication and the current state of the art in V2V communication research. The study aims to contribute to the field by comprehensively understanding the implementation of V2V communication in intelligent traffic systems and informing potential future research in this area. V2V communication can improve road safety and traffic flow in intelligent traffic systems. However, more research is needed to address the challenges and develop advanced and cost-effective V2V communication systems.

Student impressions of instructors based on Zoom backgrounds: investigating perceived technology skills of instructors and affective learning of students

The purpose of this study is to identify how Zoom backgrounds affect students’ affective learning and perceptions of an instructor’s technology use skills in online learning experiences. Data collected from undergraduate students in the U.S. indicate that with certain Zoom backgrounds, male students perceive the instructor having lower technology skills and experience less affective learning towards the instructor and course content than do female students. Overall, the study’s findings provide meaningful contributions to instructional communication research and suggest recommendations for strategic use of Zoom backgrounds to cultivate the best impression of an instructor and positive learning experiences.