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This study examined the effects of SNS users' perceived information overload on SNS fatigue and mental health, highlighting the influence of users' attachment styles. Also, the mediating role of SNS fatigue in the association between perceived information overload and mental health was investigated. Using data from a national sample in South Korea (N = 635), the study found that those in the secure style (n = 216) and the dismissing style (n = 134) showed low levels of perceived information overload and SNS fatigue than those in the preoccupied style (n = 143) and the fearful style (n = 160). These results uncovered that the anxiety dimension of attachment styles was the differentiating factor for the variables in the study. Moreover, the study supported the mediating role of SNS fatigue in the three attachments styles except for the fearful style. Theoretical implications and contributions of the study were also discussed. [ABSTRACT FROM AUTHOR]

The article investigates how and when the two first movers in knowledge-based regulation – the OECD and the World Bank – developed policy brokerage as an instrument of global governance in the education sector. We also examine how their target clientele – national governments – responds to this instrument. Given the surplus of research evidence in today's digital economy, intergovernmental organisations have the challenge of standing out as trusted and credible knowledge brokers in a crowded space. The authors make the case for a comparative research programme – tentatively labeled 'Governance by Numbers 2.0' – that is informed by a multidisciplinary (history, political science, interdisciplinary policy studies) interpretive framework and that advances a transnational, relational method of inquiry which draws attention to the global/national nexus. [ABSTRACT FROM AUTHOR]

Purpose: This study constructed an information search process model based on costs and benefits to reflect different information search processes under different decisions from a behavioural economics perspective. Design/methodology/approach: This study used a deductive approach to conceptualise the costs, benefits, and uncertainties of the information search process. Subsequently, we constructed an information search process model based on the costs and benefits using graphical reasoning, loss aversion theory, bounded rationality theory, the satisficing theory of behavioural economics, and the uncertainty changes of information search process. Findings: The model revealed four types of user behaviours in the information search process: (1) avoiding search at the initiation of the search process; (2) exiting in the middle of a search; (3) stopping at the point of satisficing; and (4) continuing the search until experiencing physical discomfort. Originality/value: The model constructed in this study treats the information search as a process based on costs and benefits with uncertainty. This model integrates information search avoidance and stopping into an information search process model. The model identifies users' bounded rationality by evaluating ideal and real situations. Moreover, the model explains relative and absolute information overloads and the area beyond the user's bounded rationality. These findings could help improve users' information literacy and optimise information systems. [ABSTRACT FROM AUTHOR]

In today's dynamic world of information overload and conflict situations of different nature, the emotional stress state is increasingly growing and encompassing all social groups. In the European Union, work stress is the second most common health problem after diseases of the musculoskeletal system and its prevention is one of the priorities of the EU Member States. By definition, stress is a physiological and psychological process by which an individual reacts to events or situations that place increased demands and pressure on him or her. Occupational stress arises in the interactions of people and their occupations. For more than thirty years it has been the subject of attention of scientists, researchers, organizations, and the general public. Burnout syndrome is the end result of a prolonged process of exhaustion in which motivated and committed individuals lose desire and energy in meeting their work goals. The phenomenon of 'professional burnout' does not occur suddenly, but is a cumulative process [ABSTRACT FROM AUTHOR]

Numerous universities nationwide announced urgent implementation of closed campus management due to the epidemics of COVID-19 in Chinese universities since March 2022, and a large number of students were under quarantine. This study aims to explore how embodied experiences (i.e., centralized quarantine and self-quarantine) and mediated experiences (i.e., exposure to media sources, pandemic information overload, and online help seeking) influence the acquisition of learned helplessness during the campus epidemics among the Chinese university students, besides, how do these two types of experiences interact with each other to elicit learned helplessness is another interested research question. The data was collected nationwide via an online survey platform from March 22nd to April 16 2022 immediately after the outbreak of campus epidemics. A total of 1267 valid student samples were retained. Hierarchical regression analysis showed that embodied experience of centralized quarantine is positively related to learned helplessness. Mediated experience of information access from friends on social media and government official media as well as online help seeking are negatively related to learned helplessness. Information access from overseas media and pandemic information overload are positively related to learned helplessness. Besides, the interaction between self-quarantine and pandemic information overload is positively related to learned helplessness. Theoretical contributions and intervention strategies aimed at enhancing authoritative communication and managing information overload during public health crisis were discussed. [ABSTRACT FROM AUTHOR]

When parents are expected to play a significant role in the management of their children's health perioperatively, information overload for parents could have particularly detrimental consequences. Our study investigated information communication and overload in 380 parents of children undergoing any elective surgical procedure at our institution. Participants completed an online questionnaire and were asked to respond to a newly designed Information Overload scale based on a modified 5 item Cancer Information Overload Scale and an 8-item atrial fibrillation information overload scale. Nineteen respondents (5%) identified as Aboriginal or Torres Strait Islander. More than a quarter of respondents (n = 102, 27%) primarily spoke a language other than English at home. 56% of respondents (n = 211) indicated that neither themselves nor any of their children had undergone a similar surgery in the past. Most respondents disagreed or strongly disagreed with the majority of the 5-item Information Overload scale statements. University undergraduates had lower total information overload score on average (-1.63, p = 0.002). People who spoke a language other than English had higher total score on average (0.98, p<0.001). Semi-structured qualitative interviews including the BRIEF health literacy screening tool were conducted with 24 parents. 23 interviewees scored 17–20 points in the BRIEF health literacy screening tool, indicating they were able to read and comprehend patient education materials. Overall, parents were satisfied with the amount of information that they received. Very rarely did any parent complain of 'information overload'. Our results show that parents of children undergoing elective paediatric surgery are not suffering from information overload in general, but they do want more information on immediate and late postoperative recovery. [ABSTRACT FROM AUTHOR]

Based on the stress coping theory, the present paper aims to investigate the influence of users' networking ability and profile control ability in mitigating the negativity of social media overload. This paper argues that in the social media context, instead of discontinuance, users tend to develop comprehensive strategies and practices to manage their social media usage. Via an exploratory factor analysis (EFA) study, five practices were identified, including continuous usage, reduced usage, setting adjustment, support seeking, and information avoidance. The results show that social media overload leads to both the perception of emotional exhaustion and disturbance handling while networking and profile control ability make users focus on disturbance handling. Besides, networking ability is found to weaken the relationship between social media overload and emotional exhaustion while profile control ability exaggerates that relationship. Finally, emotional exhaustion and disturbance handling both predict users' different social media management practices. [ABSTRACT FROM AUTHOR]

China has a longstanding tradition of alcohol consumption, yet excessive drinking poses significant health risks, particularly for individuals with cardiovascular conditions such as hypertension. While existing literature indicates that both health information scanning and seeking behaviors can impact health beliefs and actions, their effects on alcohol prevention remain understudied. Utilizing data from a national survey in China, this study investigates the influence of health information scanning and seeking on alcohol risk knowledge and the frequency of excessive drinking among hypertensive drinkers. Results demonstrate that both health information scanning (b = -.018, p < .05) and seeking (b = -.030, p < .001) are negatively associated with excessive alcohol consumption indirectly through heightened awareness of alcohol as a risk factor for cancer. However, health information scanning is positively linked to excessive drinking directly (b = .203, p < .01). Additionally, cancer information overload positively moderates the relationship between awareness of alcohol as a cancer risk factor and excessive drinking (b = .148, p < .001). Hypertensive drinkers who experience lower levels of cancer information overload are more inclined to reduce excessive alcohol consumption. These findings underscore the different roles of health information scanning and seeking on alcohol control. It is important to implement interventions aimed at encouraging active information seeking and mitigating information overload. Educational programs should be promoted to help high-risk groups accurately understand the risk of excessive drinking. [ABSTRACT FROM AUTHOR]

The editorial discusses the exponential growth in scientific research publications, highlighting the challenges and opportunities it presents. The surge in publications is attributed to factors like the expansion of the global research community and the pressure to publish in academia. While the increase in research output can lead to more knowledge and discoveries, it also poses challenges such as information overload, concerns about research quality, and the need for new approaches to research evaluation. The editorial emphasizes the importance of adapting to the evolving research landscape to ensure genuine progress and quality academic research. [Extracted from the article]

Despite their ethical challenges, recommender systems (RS) are widely endorsed as a necessary solution to the problem of information overload. After clarifying how the harmful effects of information overload can be characterized in distinct ways, I explore the often overlooked potential benefits of abundant online spaces. I argue that these spaces afford valuable opportunities to experience spontaneous freedom. I then put forth a more comprehensive evaluation of the role RS should assume in algorithmically structuring the online space. This evaluation aims to reconcile the dual objectives of mitigating the harms of information overload and preserving opportunities to experience spontaneous freedom. [ABSTRACT FROM AUTHOR]

The global outbreak of COVID-19 in 2020 has led to the dominance of COVID-19 prevention information on all media channels. Drawing on the ability–motivation model of information processing, this study examined how such an information overabundance hampered individuals' ability and motivation to process in the era of COVID-19. With a survey conducted from 493 participants, we found that less message elaboration of COVID-19 prevention information was predicted by greater message fatigue, a state of low motivation due to information overabundance. In addition, greater message fatigue was accompanied by greater information overload, a state of low ability due to information overabundance. Moreover, certain motivation-related (i.e. health status, trait reactance and frequency of information seeking) and ability–related factors (i.e. health literacy, health status, trait anxiety and information quality) were found to be associated with message fatigue and information overload, respectively. The theoretical and practical implications are discussed. [ABSTRACT FROM AUTHOR]

In the UK, minority ethnic groups were reported to face the greatest risk from COVID-19. Yet, little is known about their perception and behaviour towards COVID-19 campaigns. This study used 35 semi-structured, in-depth interviews with minority ethnic adults aged 60 or over in England and Wales to explore their motivations for complying with or disregarding official guidance and their evaluations of various campaign content and channels used early in the pandemic. Using Template Analysis, key themes in the interviewees' discourse were identified, which were subsequently analysed using the Theory of Planned Behaviour (TPB). This study found that the predominant motivations for non-compliant behaviour included fatigue from information overload, government- and socially-induced distrust, as well as self-reported personality traits. In contrast, compliant individuals emphasised community-based obligations and their trust in official communications. Although participants recognised the pandemic as a challenging time, they were generally unsatisfied with the credibility, consistency, and accessibility of public health messaging. This investigation contributes to health communications studies by adopting a qualitative approach and providing insights into an under-researched demographic. [ABSTRACT FROM AUTHOR]

Researchers have long debated how radio broadcasts affected the dynamics of the 1994 genocide in Rwanda, with some arguing that the radio was highly consequential, and others suggesting such effects have been overstated. This article contributes to these debates—as well as to debates regarding the role of old and new media in collective action—by examining whether and how Radio Télévision Libre des Mille Collines (Radio RTLM) coverage was associated with two core aspects of the violence: (1) subnational onset of genocidal violence and (2) participation in genocidal violence across subnational spaces. Drawing on new data on Radio RTLM coverage, we find that areas with coverage were more likely to experience immediate onset of violence. However, our analysis of participation in the genocide—which uses more accurate measures of participation and of radio coverage than prior studies—finds no significant association between Radio RTLM coverage and subnational levels of participation. After illustrating that these results are robust to numerous model specifications, we theorize that information broadcast over the radio's airways contributed to the creation of a critical mass that initiated genocide in localized spaces. We conclude by considering the importance of understanding the role of media in the subnational onset of violence. [ABSTRACT FROM AUTHOR]

Summary: The Internet of Vehicles (IoV) is a hot research topic in intelligent transportation, and the research on new methods of intelligent data transmission is one of the key contents. Aiming at the application scenario of urban air quality monitoring data collection and transmission based on IoV, a new reliable data transmission method (Vehicular Grouping‐Communicated Data [VGCD]) based on crowd sensing strategy is proposed. This method is designed to utilize the intelligent perception and collaborative monitoring of vehicle to collect data, avoiding redundancy and overload of information; a reliable data transmission minimum delay hybrid routing method is proposed in the data transmission part, which combines encoding mechanism with routing design, integrates routing switching ideas, predicts vehicle adaptive connectivity based on fuzzy logic, and makes probability based routing decisions to minimize delay, achieving reliable and efficient data collection and transmission. The proposed new method has important theoretical significance and practical value for various applications such as dynamic remote perception monitoring based on the IoV in intelligent transportation. [ABSTRACT FROM AUTHOR]

The present study examined the predictive role of social media use on adults’ psychological distress through the mediating role of one of the digital stress factors, i.e. information overload. A sample of 295 participants aged 18–41 (M age = 21.15, SD = 3.67, 82% females) filled out self-reported questionnaires measuring social media integration, anxiety, depression, and stress symptoms, as well as cyber-based and place-based information overload. Results suggested significant associations between social media integration and emotional connection, cyber-based information overload, and psychological distress symptoms. Cyber-based information overload was positively associated with place-based information overload and psychological distress symptoms. SEM analyses suggested a partial positive and statistically significant mediation between social integration and emotional connection and psychological distress by information overload: high scores on social integration and emotional connection were marginally positively associated with high scores on information overload and with high scores on psychological distress as direct effects. However, on the second mediation path, high scores on information overload were positively associated with high scores on psychological distress, but no significant total effect was observed. We discuss the present findings considering their implications for digital stress awareness and practical strategies for preventing information overload-related negative outcomes. [ABSTRACT FROM AUTHOR]

In an era of information overload, understanding individuals' news consumption and avoidance necessitates an examination of the specific contexts in which these practices occur. While research in journalism studies has mainly underscored consumption habits at the individual level, limited scholarly attention has been given to news avoidance within the structure of dyadic spousal relationships. This study shifts the focus from individual choices to the couple as a unit of analysis, exploring how each partner's choice of media platform, content, and routines may be shaped by the context of being in a spousal relationship. Drawing on 82 interviews with Israelis, including 14 interviews with both partners of seven heterosexual couples, this study reveals three patterns of news avoidance within the context of a couple's relationship: avoiding shared news consumption, gender-based news avoidance practices, and a division of media-related responsibilities. This study contributes to a more nuanced understanding of the contextual factors shaping news avoidance by elucidating how media use and non-use unfold within social relationships. It also demonstrates how news avoidance can be perceived as a liberating choice, enabled by partners' negotiation of preferences, platforms, and routines. [ABSTRACT FROM AUTHOR]

While live commerce provides consumers with a new shopping experience, it also leads them to experience shopping failures and to develop a self-protection mechanism to prevent wrong purchases. To address this issue, merchants have attempted to explore new marketing methods for live commerce, giving rise to an offense and defense game between streamers and consumers. In this study, we sought to confirm the effectiveness of consumer protection mechanisms and the impact of streamers' information overload marketing strategy in live commerce. Accordingly, we constructed a hypothetical model based on protection motive theory and information overload theory. In addition, we analyzed the data from the simulated live streaming marketing on seven hundred people through partial least squares structural equation modeling. The results indicate that product utilitarian value uncertainty, consumers' experiential efficacy, and response costs, which are the main factors in the formation of consumer protection mechanisms, influence consumers' intention to stop their purchases. Streamers can circumvent consumer self-protection mechanisms through information overload marketing by reducing utilitarian value uncertainty and consumers' experiential efficacy and increasing consumers' response costs. However, consumers would be able to rebuild their self-protection mechanism through consumer resilience, which moderates the effects of information overload. This study's results provide important theoretical perspectives and new ideas for formulating marketing strategies for live commerce. [ABSTRACT FROM AUTHOR]

Background: In the information age of health care, nurses often face information overload, leading to negative emotions, e.g., anxiety that may impede the adoption of evidence-based practice and clinical decision-making process. Nurses with higher digital health literacy can effectively process and manage information. Despite this, no research has explored the relationship between information anxiety, digital health literacy, and core competency among nurses. Therefore, this study aims to investigate the mediating effects of digital health literacy on information anxiety and core competency among nurses. Methods: From July to October 2023, the data for this cross-sectional study were collected. The study surveyed a total of 608 nurses from three tertiary hospitals in Fujian Province, and the survey instruments included a sociodemographic information questionnaire, Chinese revision version of the Digital Health Literacy Instrument (CR-DHLI), Information Anxiety Scale (IAS), and Competency Inventory for Registered Nurses (CIRN). Descriptive statistics and Pearson correlation analysis were conducted using SPSS 29.0, and the mediating effect of digital health literacy was examined using Mplus. Results: The mean score of nurses' information anxiety, digital health literacy, and core competency was 3.03 ± 0.91, 2.46 ± 0.56, 2.72 ± 0.88, respectively. And the mediation model of information anxiety on core competency for nurses showed a good model fit index (χ²/df = 2.207, CFI = 0.985, TLI = 0.982, RMSEA = 0.045, SRMR = 0.035). Digital health literacy was positively correlated with nurses' core competency but negatively correlated with information anxiety. The results of path analysis revealed that information anxiety had negative and significant direct effects on NCC (β = -0.119, P = 0.004) and DHL (β = -0.297, P < 0.001). DHL had a positive effect on NCC (β = 0.306, P < 0.001). Digital health literacy played a partial mediating role, accounting for 43.54% of the relationship between information anxiety and nurses' core competency. Conclusions: Information anxiety among nurses was at relatively high levels, which had a negative impact on the core competency of nurses. This issue requires attention from nursing managers. The mediating role of digital health literacy in the relationship between information anxiety and core competency among nurses has been established. Nursing managers should strengthen the evaluation of nurses' DHL and devise effective support strategies to enhance DHL, thus improving the core competence of nurses in information age. [ABSTRACT FROM AUTHOR]

This study examines the information-seeking behavior of the clergy using parish pastors in the Redeemed Christian Church of God (RCCG) in Agbarho community in Delta State as a case study. The study seeks to identify the information needs, the sources of information, the purpose of the use of information, and the challenges to information seeking among RCCG parish pastors in Agbarho. A descriptive survey research design was adopted for the study. The total population for the study comprises 44 parish pastors of the RCCG in two Zones of RCCG Delta Province 4 in Agbarho Community. The entire population was used as a sample using the total enumeration sampling technique. The instrument used for data collection was a structured questionnaire. The data collected for this study were analyzed using simple percentage/frequency counts. The study found that RCCG pastors in Agbarho need and use the information for several issues such as sermon preparation, personal and church growth, church administration, evangelism, conflict resolution, meetings/programs, and personal/members' welfare among others. They get the information they need from formal sources such as the Bible, books including all RCCG publications such as Open Heavens and Sunday school manuals, magazines (RCCG Bulletins), etc. Also, RCCG pastors in Agbarho community, Delta State, Nigeria also gets information from informal sources such as senior pastors, colleagues, friends in the ministry, church members, and family among others. In their effort to seek information, RCCG pastors in Agbarho community, Delta State, Nigeria faces some challenges such as limited financial resources, lack of access to ICT facilities, language barriers, information overload, time factor, and poor awareness of information sources. The study recommends that the RCCG authorities in conjunction with other churches and community leaders should establish and equip a library in every community where they are present as a way of advancing their Christian Social Responsibilities (CSR) as this will allow their pastors to have access to free and timely information among others. [ABSTRACT FROM AUTHOR]

In recent years, online education platforms have seen rapid growth, attracting an increasing number of students to digital learning environments. In online education, learners can choose learning content and plan their own learning path more freely. Although the online education platform gives learners a high degree of freedom, it reduces the learning guidance for learners, which leads to problems such as "information overload" and "knowledge loss". The main manifestation is that learners don't know how to plan their learning path, resulting in reduced learning efficiency and poor learning effects. To address these challenges, this paper proposes a learning path recommendation algorithm based on reinforcement learning called RLLP. The RLLP model takes into account the learner's learning goals, knowledge level, and the relationships between knowledge points. Simultaneously, it also considers the smoothness of the learning path and the learner's engagement, aiming to recommend efficient and sensible learning paths to learners. Extensive experimental results demonstrate the effectiveness of RLLP model. [ABSTRACT FROM AUTHOR]

Sharing of misinformation on social media platforms is a global concern, with research offering little insight into the motives behind such sharing. Drawing from the cognitive load theory and literature on cognitive ability, we developed and tested a research model hypothesising why people share misinformation. We also tested the moderating role of cognitive ability. We obtained data from 385 social media users in Nigeria using a chain referral technique with an online questionnaire as the instrument for data collection. Our findings suggest that information overload and social media fatigue are strong predictors of misinformation sharing. Information stress also contributed to misinformation sharing behaviour. Furthermore, cognitive ability moderated and weakened the effect information strain and information overload have on misinformation sharing in such a way that this effect is more pronounced among those with low cognitive ability. This indicates that those with low cognitive ability have a higher tendency to share misinformation. However, cognitive ability had no effect on the effect social media fatigue has on misinformation sharing behaviour. The study concluded with some theoretical and practical implications. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to examine how the interplay of stressor (e.g. fear of missing out, FoMO) and strains (e.g. perceived social overload, communication overload, information overload and system feature overload) in social networking sites (SNS) use can contribute to users' SNS fatigue from a configurational view. Design/methodology/approach: Data were collected among 363 SNS users in China via an online survey, and fuzzy-set qualitative comparative analysis (fsQCA) was applied in this study to scrutinize the different combinations of FoMO and overload that contribute to the same outcome of SNS fatigue. Findings: Six combinations of casual conditions were identified to underlie SNS fatigue. The results showed that FoMO, perceived information overload and system feature overload are the core conditions that contribute to SNS fatigue when combined with other types of overloads. Originality/value: The current work supplements the research findings on SNS fatigue by identifying the configurations contributing to SNS fatigue from the joint effects of stressor (FoMO) and strain (perceived social overload, communication overload, information overload and system feature overload) and by providing explanations for SNS fatigue from the configurational perspective. [ABSTRACT FROM AUTHOR]

AbstractWomen are increasingly turning to mHealth apps as primary sources for breastfeeding education and support. The rising prevalence of mHealth apps presents a unique opportunity to explore their impact on women’s breastfeeding experiences. Understanding user perspectives of these apps, especially focusing on their persuasive design aspects, can offer valuable insights for enhancing maternal and child health outcomes. These insights can optimize these technologies to align with user values and promote sustained healthy behaviors. This study aimed to undertake an empirical exploration of users’ experiences with the persuasive design features employed in the Milky Way mHealth app and align the findings with human values within the value-sensitive design (VSD) framework. Semi-structured interviews were conducted with a group of women who had used the Milky Way app. Interview data were analyzed using an inductive thematic approach. To provide insight into users’ values mediated by the app, a deductive analysis complemented by a data-driven inductive approach was performed. Data analysis was supported by NVivo data-management software. Findings from the study demonstrate that the persuasive design elements in the Milky Way app significantly influence users’ experiences. The analysis provided four primary themes: Informative, Easy to use, Credible, and Social connection. Overall, participants praised the app’s trustworthy educational content and support features as valuable resources for addressing breastfeeding challenges and obtaining reliable support. Participants expressed concerns about information overload and emphasized the importance of personalized support and evidence-based tailored recommendations. The results demonstrated that users’ values were expressed and embedded within the app. The analysis indicated an alignment between the app design features and the values and opinions of the users within the VSD framework. This study interprets women’s perspectives utilizing the Milky Way app and highlights the significance of its evidenced-based educational and support features. Further investigation into potential user values like privacy, remains crucial for a comprehensive user-centered app design. The empirical insights gained from this study contribute to future research, informing the development and design of ethically considerate persuasive mHealth apps to maintain their relevance in promoting positive user experiences and facilitating meaningful behavior change. [ABSTRACT FROM AUTHOR]

Although social commerce induces consumers' impulse purchase behavior, no work has been done to examine the impacts of different uses of social commerce on online impulse purchase and their influencing mechanisms. Grounded on the stimulus-organism-response theory, this study explored the relationships between cognitive use (CU), hedonic use (HU), and social use (SU) of social commerce (SC) and online impulse purchase (OIP) and technostress (TS), with mediating effect of social capital and information overload (IO). Non-probability purposive samples of 693 respondents were collected via a questionnaire survey in different provinces of China, and the data were scrutinized with Smart Partial Least Squares (SmartPLS). The results reveal that SU, CU, and HU positively affect social bridging (SBR), social bonding (SBO), and IO. Furthermore, SBR and SBO positively influence OIP, but SBO negatively influences TS. Moreover, IO positively influences TS but negatively influences OIP. Additionally, TS hurts OIP. This is the first study that incorporated different uses of social commerce (i.e., SU, CU, and HU) and investigated their positive and adverse effects on OIP. The study helps understand SC uses' influencing mechanisms on customers' OIP. The results show the positive role of social capital (i.e., SBR and SBO) in enhancing OIP. It also shows that improper and uncontrolled use of SC could lead to stress or switching behavior. The research also offers guidelines for managers to grow more constructive tactics for promoting consumers' impulse purchases. [ABSTRACT FROM AUTHOR]

The fast growth of the web generates a significant amount of heterogeneous information such as images, text, audio, and video through various applications. These applications use different layouts to represent significant information. The layouts of table information are overloaded with anomalies that have given rise to intensive research into the semantification of web content and organizing tabular data for knowledge sharing and acquisition. Moreover, there are many anomalies present in tabular layouts that lead to the lack of semantic representation in tabular form and new challenges in data modeling. In this paper, we have discussed the various anomalies present in the tabular data that pertain to ontology learning and population tasks and provide the semantification of tabular data. To complete this task, (1) we provide the list of anomalies that pertain to semantification and provide the resolution to anomalies along with the semantification of tabular data, and (2) we have established the algorithm to interpret the table structure into a formal representation to analyze anomalies and provide the resolution. Furthermore, the proposed approach has been compared with existing approaches using ontology elements, the ability to resolve the anomalies, and the time complexity of the ontology population. [ABSTRACT FROM AUTHOR]

Research has neglected to consider the news as a source of work-related information that might impact employee experiences and outcomes. In an initial pilot study with a diverse cross-section of employees, we confirm that deriving work-related insights from the news, either intentionally or serendipitously, is a common occurrence. Next, drawing from conservation of resources theory, we developed a model to examine both the beneficial and detrimental consequences associated with job-relevant news consumption. We conducted a 10-day experience sampling study which showed that job-relevant news consumption increases information overload but also produces perceived learning. Information overload, perceived learning, and emotional exhaustion serially mediate the relationship between consumption of job-relevant news and employee withdrawal behavior. Furthermore, perceived learning buffers the indirect relationship between news consumption and work withdrawal via information overload and emotional exhaustion. We discuss the theoretical and practical implications of our research. [ABSTRACT FROM AUTHOR]

Patients consistently rate cancer-related fatigue (CrF) as the most prevalent and debilitating symptom. CrF is an important but often neglected patient concern, partly due to barriers to implementing evidence-based interventions. This study explored what an ideal intervention for CrF would look like from the perspectives of different stakeholders and the barriers to its implementation. Three participant populations were recruited: healthcare providers (HCPs; n = 32), community support providers (CSPs; n = 14), and cancer patients (n = 16). Data were collected via nine focus groups and four semi-structured interviews. Data were coded into themes using content analysis. Two main themes emerged around addressing CrF: "It takes a village" and "This will not be easy". Participants discussed an intervention for CrF could be anywhere, offered by anyone and everyone, and provided early and frequently throughout the cancer experience and could include peer support, psychoeducation, physical activity, mind–body interventions, and interdisciplinary care. Patients, HCPs, and CSPs described several potential barriers to implementation, including patient barriers (i.e., patient variability, accessibility, online literacy, and overload of information) and systems barriers (i.e., costs, lack of HCP knowledge, system insufficiency, and time). As CrF is a common post-treatment symptom, it is imperative to offer patients adequate support to manage CrF. This study lays the groundwork for the implementation of a patient-centered intervention for CrF in Canada and possibly elsewhere. [ABSTRACT FROM AUTHOR]

Recommender system helps address information overload problem and satisfy consumers' personalized requirement in many applications such as e-commerce, social networks, and in-game store. However, existing approaches mainly focus on improving the accuracy of recommendation tasks but usually ignore how to improve the interpretability of recommendation, which is still a challenging and crucial task, especially for some complicated scenarios such as large-scale online games. A few previous attempts on explainable recommendation mostly depend on a large amount of a priori knowledge or user-provided review corpus, which is labor consuming as well as often suffers from data deficiency. To relieve this issue, we propose a Multi-source Heterogeneous Graph Attention Network for Explainable Recommendation (MHANER) for the case without enough a priori knowledge or corpus of user comments. Specifically, MHANER employs the attention mechanism to model players' preference to in-game store items as the support for the explanation of recommendation. Then a graph neural network–based method is designed to model players' multi-source heterogeneous information, including the players' historical behavior data, historical purchase data, and attributes of the player-controlled character, which is leveraged to recommend possible items for players to buy. Finally, the multi-level subgraph pattern mining is adopted to combine the characteristics of a recommendation list to generate corresponding explanations of items. Extensive experiments on three real-world datasets, two collected from JD and one from NetEase game, demonstrate that the proposed model MHANER outperforms state-of-the-art baselines. Moreover, the generated explanations are verified by human encoding comprised of hard-core game players and endorsed by experts from game developers. [ABSTRACT FROM AUTHOR]

This article develops a model showing how information reporters influence information load among decision makers and generate supplier-induced information demand (SID). The intra-corporate information-providing process is an expert market with information asymmetry. I show that information overload occurs as an SID and is the result of informational overconsumption deliberately caused by the supplying reporter. My analysis highlights that the information overload depends on the specificity of information. It also shows that the decision maker may face a hold-up situation in light of switching costs. The more specific the information needed, the higher the threat of information overload. The strategic content of information tempts reporting managers to overload the decision maker for the purpose of increasing their reporting transfer price and to discourage the decision maker from getting the information from another reporting manager. Although the decision maker knows a part of the information demand, information overload involves the cost of using unnecessary inputs, information overload occurs as an SID of information, even if other competing reporting managers exist. My analysis demonstrates that information overload can occur due to uncertainty and opportunism of both the decision maker and reporting managers. [ABSTRACT FROM AUTHOR]

AbstractIn today’s era of information overload, efficiently extracting valuable information from a large volume of textual data has become a crucial challenge in reading. This study aimed to explore the enhancement of Chinese readability in the digital domain through intelligent typesetting method. This study involved two experiments. The purpose of the first experiment was to achieve the machine learning-based assessment of the importance of individual words in Chinese articles and to automate typesetting based on the importance of words. For the second experiment, readability tests and eye-tracking reading tests were performed and the reading performance and reading attention between intelligent typesetting and general typesetting style was compared. This work proposed three Chinese typesetting methods that distinguished the importance of Chinese text information, based on font size and color. The results showed that first, when reading Chinese text, visual attention was more likely to be drawn to larger font sizes, darker brightness, or warmer-colored characters. Second, intelligent Chinese typography that distinguishes information importance through font size, color brightness, and color hue can enhance Chinese reading comprehension accuracy and subjective evaluation. It was concluded that using the TextRank model to distinguish importance of Chinese vocabulary and intelligent typesetting methods based on visual features of font could obviously improve text readability. Specifically, readability achieved through intelligent typesetting method distinguishing information importance through font color brightness surpasses that of general typesetting significantly. These intelligent typesetting methods can be widely applied in Chinese reading scenarios, such as web pages, e-books, information visualization, and other Chinese reading contexts. [ABSTRACT FROM AUTHOR]

Background: The growing abundance of in vitro omics data, coupled with the necessity to reduce animal testing in the safety assessment of chemical compounds and even eliminate it in the evaluation of cosmetics, highlights the need for adequate computational methodologies. Data from omics technologies allow the exploration of a wide range of biological processes, therefore providing a better understanding of mechanisms of action (MoA) related to chemical exposure in biological systems. However, the analysis of these large datasets remains difficult due to the complexity of modulations spanning multiple biological processes. Results: To address this, we propose a strategy to reduce information overload by computing, based on transcriptomics data, a comprehensive metabolic sub-network reflecting the metabolic impact of a chemical. The proposed strategy integrates transcriptomic data to a genome scale metabolic network through enumeration of condition-specific metabolic models hence translating transcriptomics data into reaction activity probabilities. Based on these results, a graph algorithm is applied to retrieve user readable sub-networks reflecting the possible metabolic MoA (mMoA) of chemicals. This strategy has been implemented as a three-step workflow. The first step consists in building cell condition-specific models reflecting the metabolic impact of each exposure condition while taking into account the diversity of possible optimal solutions with a partial enumeration algorithm. In a second step, we address the challenge of analyzing thousands of enumerated condition-specific networks by computing differentially activated reactions (DARs) between the two sets of enumerated possible condition-specific models. Finally, in the third step, DARs are grouped into clusters of functionally interconnected metabolic reactions, representing possible mMoA, using the distance-based clustering and subnetwork extraction method. The first part of the workflow was exemplified on eight molecules selected for their known human hepatotoxic outcomes associated with specific MoAs well described in the literature and for which we retrieved primary human hepatocytes transcriptomic data in Open TG-GATEs. Then, we further applied this strategy to more precisely model and visualize associated mMoA for two of these eight molecules (amiodarone and valproic acid). The approach proved to go beyond gene-based analysis by identifying mMoA when few genes are significantly differentially expressed (2 differentially expressed genes (DEGs) for amiodarone), bringing additional information from the network topology, or when very large number of genes were differentially expressed (5709 DEGs for valproic acid). In both cases, the results of our strategy well fitted evidence from the literature regarding known MoA. Beyond these confirmations, the workflow highlighted potential other unexplored mMoA. Conclusion: The proposed strategy allows toxicology experts to decipher which part of cellular metabolism is expected to be affected by the exposition to a given chemical. The approach originality resides in the combination of different metabolic modelling approaches (constraint based and graph modelling). The application to two model molecules shows the strong potential of the approach for interpretation and visual mining of complex omics in vitro data. The presented strategy is freely available as a python module (https://pypi.org/project/manamodeller/) and jupyter notebooks (https://github.com/LouisonF/MANA). [ABSTRACT FROM AUTHOR]

AbstractDrawing on the stressor–strain–outcome (SSO) framework, this study examined how information-related stressors (perceived information overload, information quality deterioration, and information narrowing) and privacy-related stressor (perceived privacy risk) in using news platforms’ recommendation algorithms trigger users’ psychological reactance, which leads to their active coping, expressive coping, or avoidance coping with their stress in using such recommendation algorithms. Using a sample of 352 valid research responses, this study found that users’ psychological reactance is positively influenced by perceived information quality deterioration, followed by perceived information overload and perceived privacy risk. Meanwhile, perceived information narrowing has no significant impact on psychological reactance. In turn, psychological reactance exerts a stronger impact on expressive coping and avoidance coping responses than on active coping response. This study enriches the literature on the stress in algorithm usage at the individual level and provides practical insights for the providers of news platforms which have applied recommendation algorithms. [ABSTRACT FROM AUTHOR]

The use of Internet for constant connectivity with social networking sites has negative consequences in the form of higher mental pressure, low physical and offline activities, and mental tiredness and fatigue. Using these given phenomena, this research explores how system complexity, information overload, and communication overload are decisive factors of tiredness of social networking sites among Chinese individuals. The study also adds the role of workfamily balance as a predictor in determining the tiredness levels of the use of social networking sites. A survey questionnaire was conducted over a sample of 507 respondents, drawn through non-probability purposive sampling techniques from employees of major Chinese organizations. The Structural Equation Modelling measurements revealed that, except for system complexity, the impact of information overload, communication overload, and work-family balance is significant in causing tiredness of social networking sites. However, while both overload factors were responsible for greater tiredness, a higher balance between work and family tends to reduce it. The study suggests that policymakers should develop strategies through to reduce such tiredness. It was also felt that a more work-family balance should be a panacea for such tiredness among the Chinese people. [ABSTRACT FROM AUTHOR]

In today's information age, personalized recommendations have permeated every aspect of people's lives, becoming an indispensable service on major mainstream websites. By considering users' past interaction habits and preferences, personalized recommendation systems cater to the unique needs of individuals, presenting content that aligns with their interests. However, research on news recommendations, compared to fields such as ecommerce and music, remains relatively scarce and faces significant challenges, particularly in identifying news choices that may engage readers amidst information overload. This study designed and implemented a personalized hot news recommendation mechanism based on collaborative filtering technology. The system was developed using the SSM framework, incorporating software engineering principles with UML modeling. The front-end interface was built and deployed using the Bootstrap framework, while the back-end interface construction was supported by the Layui front-end framework. MySQL served as the storage system for news information. The core services of the personalized news push system include user account creation and login, personal information management, information search, news content evaluation, customized content push, and administrator-end information supervision. The customized push service, in particular, relies on collaborative filtering technology, tag-based recommendation strategies, and mechanisms for tracking current hot topics to achieve its goals. [ABSTRACT FROM AUTHOR]

With growing numbers of workers relying on the digital workplace to get work done, attention is increasingly focused on the well-being impacts of digital working. This study explored the stress, burnout and mental health implications of employees' digital workplace experience. Using the Job Demands-Resources model as a theoretical foundation, 142 workers were surveyed about their experiences of dark side of digital working effects (stress, overload, anxiety, and Fear of Missing Out) and well-being (exhaustion and mental health). Results from regression analyses indicated that the fear of missing out on information (IFoMO) is a risk factor for employee mental health and, along with information overload (IO), may lead to greater exhaustion. Additionally, both IFoMO and IO elevate digital workplace stress, further impacting well-being negatively. The results suggest that organizations need to optimize the flow of work-related information in the digital workplace and support employees to leverage information effectively. Plain language summary: Impacts to employee well-being due to information in the digital workplace With growing numbers of workers relying on the digital workplace to get work done, attention is increasingly focused on the well-being impacts of digital working. This study explored stress, burnout and mental health issues that can arise for employees as a result of demands they experience when using technology at work. A total of 142 workers were surveyed about stress, overload, anxiety, and Fear of Missing Out relating to technology use. They were also asked about negative well-being impacts namely exhaustion and mental health issues. Results indicated that the fear of missing out on information is a risk factor for employee mental health and, along with information overload, may lead to greater exhaustion. In addition, both of these information related issues were found to elevate digital workplace stress, further impacting well-being negatively. The results suggest that organizations need to optimize the flow of work-related information in the digital workplace and support employees to leverage information effectively. [ABSTRACT FROM AUTHOR]

This study examines the impact of message length and audience's perceived information overload on the effectiveness of a fact-check in reducing belief in fake news within the COVID-19 vaccination context. Through an online experiment (N = 374) conducted in Singapore, we found an interaction effect between one's level of information overload and the type of fact-check that was being shown (short, medium, or long). The findings from this study help to extend the literature on the effectiveness of fact-checks in reducing general public's belief in fake news. [ABSTRACT FROM AUTHOR]

While comprehensive knowledge networks can be instrumental in finding solutions to complex problems or supporting the development of detailed simulation models, their large number of nodes and edges can become a hindrance. When the representation of a network becomes opaque, they stop fulfilling their role as a shared representation of a system between participants and modelers; hence, participants are less engaged in the model-building process. Combating the information overload created by large conceptual models is not merely a matter of changing formats: shifting from an unwieldy diagram to enormous amounts of text does not promote engagement. Rather, we posit that participants need an environment that provides details on demand and where interactions with a model rely primarily on a familiar format (i.e., text). In this study, we developed a visual analytics environment where linked visualizations allow participants to interact with large conceptual models, as shown in a case study with hundreds of nodes and almost a thousand relationships. Our environment leverages several advances in generative AI to automatically transform (i) a conceptual model into detailed paragraphs, (ii) detailed text into an executive summary of a model, (iii) prompts about the model into a safe version that avoids sensitive topics, and (iv) a description of the model into a complementary illustration. By releasing our work open source along with a video of our case study, we encourage other modelers to use this approach with their participants. Their feedback and future usability studies are key to respond to the needs of participants by improving our environment given individual preferences, models, and application domains. [ABSTRACT FROM AUTHOR]

Purpose: Under the background of coexistence of information overload and information fragmentation, it is of great significance to identify influencing factors and reveal the evolution logic of public opinion for public opinion governance. Design/methodology/approach: Taking 24 hot social events as research cases, firstly, the evolution process of public opinion was divided into initial stage and response stage. Secondly, eight antecedent variables were extracted for qualitative comparative analysis of fuzzy sets. Finally, the configuration path of public opinion evolution results was summarized. Findings: The research showed that compared with the initial stage, the influencing factors in the reaction stage played a key role in the continuous evolution of public opinion. The influencing factors in the initial stage and response stage played an indispensable role in promoting the evolution of public opinion to calm down. Practical implications: This research can provide reference for regulators to timely grasp the initiative, discourse power and leadership of public opinion development. Originality/value: Research on the two-stage configuration path of public opinion evolution is helpful to clarify the key factors affecting the evolution trend of online public opinion of hot events. [ABSTRACT FROM AUTHOR]

Purpose: Based on the C-A-C framework, this article examined users' information avoidance intention in social media platforms. Design/methodology/approach: The authors conducted data analysis using a mixed method of the SEM and fsQCA. Findings: The results indicated that information overload, functional overload and social overload influence fatigue and dissatisfaction, both of which further determine users' information avoidance intention. The results of the fsQCA identified two paths that trigger users' information avoidance intention. Originality/value: Extant studies have examined the information avoidance in the contexts of healthcare, academics and e-commerce, but have seldom explored the mechanism underlying users' information avoidance in social media. To fill this gap, this article will empirically investigate users' information avoidance in social media platforms based on the C-A-C framework. [ABSTRACT FROM AUTHOR]

This study examines how intrinsic message characteristics (i.e. call to action, negative emotions, and informality) drive online information engagement (i.e. the numbers of likes and retweets). We also explore how the veracity of information (i.e. misinformation vs. accurate information) is intertwined with negative emotions in promoting online information engagement. Analyses of 472 tweets demonstrate that tweets with higher anger-laden words were more likely to be retweeted. By contrast, those with higher anxiety-laden words and more informal language were more likely to receive likes. Regarding the interaction between distinct emotions and the veracity of information, the results showed that anger-laden misinformation tended to be retweeted more and received more likes from users whereas anger-laden accurate information received fewer likes. Further, anxiety-laden accurate information received more likes. This study contributes to existing scholarship surrounding online information engagement by illustrating how intrinsic message features are differentially associated with liking and retweeting behaviours. Our findings also provide practical implications on how messages should be tailored to encourage engagement on social media and devise effective countermeasures to curb the potentially detrimental effects of anger when used for the purposes of misinformation. [ABSTRACT FROM AUTHOR]

The number of scientific publications nowadays is rapidly increasing, causing information overload for researchers and making it hard for scholars to keep up to date with current trends and lines of work. Recent work has tried to address this problem by developing methods for automated summarization in the scholarly domain, but concentrated so far only on monolingual settings, primarily English. In this paper, we consequently explore how state-of-the-art neural abstract summarization models based on a multilingual encoder–decoder architecture can be used to enable cross-lingual extreme summaries of scholarly texts. To this end, we compile a new abstractive cross-lingual summarization dataset for the scholarly domain in four different languages, which enables us to train and evaluate models that process English papers and generate summaries in German, Italian, Chinese and Japanese. We present our new X-SCITLDR dataset for multilingual summarization and thoroughly benchmark different models based on a state-of-the-art multilingual pre-trained model, including a two-stage pipeline approach that independently summarizes and translates, as well as a direct cross-lingual model. We additionally explore the benefits of intermediate-stage training using English monolingual summarization and machine translation as intermediate tasks and analyze performance in zero- and few-shot scenarios. Finally, we investigate how to make our approach more efficient on the basis of knowledge distillation methods, which make it possible to shrink the size of our models, so as to reduce the computational complexity of the summarization inference. [ABSTRACT FROM AUTHOR]

In an era overwhelmed by academic big data, students grapple with identifying academic papers that resonate with their learning objectives and research interests, due to the sheer volume and complexity of available information. This study addresses the challenge by proposing a novel academic paper recommendation system designed to enhance personalized learning through the nuanced understanding of academic social networks. Utilizing the theory of social homogeneity, the research first constructs a sophisticated academic social network, capturing high-order social relationships, such as co-authorship and advisor–advisee connections, through hypergraph modeling and advanced network representation learning techniques. The methodology encompasses the development and integration of a hypergraph convolutional neural network and a contrastive learning framework to accurately model and recommend academic papers, focusing on aligning with students' unique preferences and reducing reliance on sparse interaction data. The findings, validated across multiple real-world datasets, demonstrate a significant improvement in recommendation accuracy, particularly in addressing the cold-start problem and effectively mapping advisor–advisee relationships. The study concludes that leveraging complex academic social networks can substantially enhance the personalization and precision of academic paper recommendations, offering a promising avenue for addressing the challenges of academic information overload and fostering more effective personalized learning environments. [ABSTRACT FROM AUTHOR]

Young children are biased to treat new information communicated to them as conventional, shareable, and known by others in their community. However, some information is privileged in the sense that is not intended to be shared with or known by all. The current study compared judgements regarding sharing conventional versus privileged information. Seventy‐four 3‐ to 5‐year‐olds and adults responded to vignettes in which a protagonist had to decide whether to share conventional (an object name) or privileged information (surprise). Consistent with our hypothesis, there was no developmental change in sharing judgements for conventional information but a clear decrease with age for sharing privileged information. Nonetheless, even 3‐year‐olds were more likely to judge that conventional information should be shared more than privileged information, though this difference increased with age. While children overall treat information as shareable, there is an emerging ability to distinguish how conventional versus privileged information should be shared. [ABSTRACT FROM AUTHOR]

This article discusses the history of reference tools in medicine, tracing their evolution from textbooks and reference files to pocket guides and smartphones. It highlights the ways in which physicians have relied on these tools as repositories of knowledge and how they have shaped medical education and practice. The article also explores the challenges and benefits of digitization and the integration of technology in reference tools. Overall, it emphasizes the importance of reference tools in the medical field and how they have evolved over time. [Extracted from the article]

Journalistic routines in the current context of information overload and communicative complexity have resulted in an excessive workload for media professionals. This issue is particularly critical in wartime situations, where the conflicting parties contribute to the problem by disseminating biased information and hoaxes within the official communication under the pretext of safeguarding their military and strategic interests. Safeguarding against disinformation and fake news has become a priority in media newsrooms. This article explores how journalists at the Spanish broadcasters À Punt and Tele 5 address the problem of news coverage concerning the wars in Ukraine and Gaza. [ABSTRACT FROM AUTHOR]

Typically, in standardised tests, girls underperform boys in mathematics while boys underperform girls in reading. Can these educational inequalities be driven by specific testing practices? This study addresses this question by innovatively using data from the largest worldwide standardized test and exploiting the random variation in the format of the tests assigned to students. I find that there is a noticeable widening of the gender gap when a larger share of questions is multiple-choice, rather than filling-the-gap questions. A 10 percentage point increase in the share of multiple-choice questions inflates female under-performance in mathematics by 0.025 standard deviations and male under-performance in reading by 0.035 standard deviations. This accounts for nearly one-quarter of the overall gender disparity found in these subjects. I provide suggestive evidence that ruling out alternative options, rather than coming up with an entire answer, may contribute to cognitive information overload among students with lower confidence levels (generally girls in mathematics and boys in reading). These cognitive loads, in turn, have implications for a student's future level of effort and performance. [ABSTRACT FROM AUTHOR]

Purpose: To examine the relationships among health literacy, risk perceptions, COVID-19 information overload, health information seeking, and race/ethnicity. Design: A cross-sectional non-probability community survey conducted between December 2020 and January 2021. A questionnaire was developed in collaboration with a local minority health task force. Setting: Albany, New York, USA. Sample: 331 adults residing in Albany, NY and neighboring areas (80.3% completion rate). Measures: Multi-item scales were used to measure health literacy, perceived severity, perceived susceptibility, information overload, and health information seeking frequency and types. Analysis: We conducted multivariate regression analysis. Results: Health literacy (standardized β = −.33, P <.001) and perceived severity (β = −.23, P <.001) were negatively associated with information overload. Information overload was negatively associated with health information seeking frequency (β = −.16, P <.05) and types (β = −.19, P <.01). A further analysis shows several factors, including information overload and race (African Americans), were negatively related to seeking specific types of information. Conclusion: We find that low health literacy and perceived severity contribute to information overload and that information overload adversely affects health information seeking. Black individuals are less likely to search for certain types of information. The cross-sectional study design limits our ability to determine causality. Future research should employ panel data to determine the directionality of the observed relationships. [ABSTRACT FROM AUTHOR]