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Under the background of open science, this paper integrates altmetrics data and combines multiple evaluation methods to analyze and evaluate the indicators' characteristics of discourse leading for academic journals, which is of great significance to enrich and improve the evaluation theory and indicator system of academic journals.

This paper obtained 795,631 citations and 10.3 million altmetrics indicators data for 126,424 published papers from 151 medicine, general and internal academic journals. In this paper, descriptive statistical analysis and distribution rules of evaluation indicators are first carried out at the macro level. The distribution characteristics of evaluation indicators under different international collaboration conditions are analyzed at the micro level. Second, according to the characteristics and connotation of the evaluation indicators, the evaluation indicator system is constructed. Third, correlation analysis, factor analysis, entropy weight method and TOPSIS method are adopted to evaluate and analyze the discourse leading in medicine, general and internal academic journals by integrating altmetrics. At the same time, this paper verifies the reliability of the evaluation results.

Six features of discourse leading integrated with altmetrics indicators are obtained. In the era of open science, online academic exchanges are becoming more and more popular. The evaluation activities based on altmetrics have fine-grained and procedural advantages. It is feasible and necessary to integrate altmetrics indicators and combine the advantages of multiple methods to evaluate the academic journals' discourse leading of which are in a diversified academic ecosystem.

This paper uses descriptive statistical analysis to analyze the distribution characteristics and distribution rules of discourse leading indicators of academic journals and to explore the availability of altmetrics indicators and the effectiveness of constructing an evaluation system. Then, combining the advantages of multiple evaluation methods, The author integrates altmetrics indicators to comprehensively evaluate the discourse leading of academic journals and verify the reliability of the evaluation results. This paper aims to provide references for enriching and improving the evaluation theory and indicator system of academic journals.

This paper aims to analyze the relationships between discourse leading indicators and citations from perspectives of integrating altmetrics indicators and tries to provide references for comprehending the quantitative indicators of scientific communication in the era of open science, constructing the evaluation indicator system of the discourse leading for academic journals and then improving the discourse leading of academic journals.

Based on the theory of communication and the new pattern of scientific communication, this paper explores the formation process of academic journals' discourse leading. This paper obtains 874,119 citations and 6,378,843 altmetrics indicators data from 65 international multidisciplinary academic journals. The relationships between indicators of discourse leading (altmetrics) and citations are studied by using descriptive statistical analysis, correlation analysis, principal component analysis, negative binomial regression analysis and marginal effects analysis. Meanwhile, the connotation and essential characteristics of the indicators, the strength and influence of the relationships are further analyzed and explored. It is proposed that academic journals' discourse leading is composed of news discourse leading, social media discourse leading, peer review discourse leading, encyclopedic discourse leading, video discourse leading and policy discourse leading.

It is discovered that the 15 altmetrics indicators data have a low degree of centralization to the center and a high degree of polarization dispersion overall; their distribution patterns do not follow the normal distributions, and their distributions have the characteristics of long-tailed right-peaked curves. Overall, 15 indicators show positive correlations and wide gaps exist in the number of mentions and coverage. The academic journals' discourse leading significantly affects total cites. When altmetrics indicators of international mainstream academic and social media platforms are used to explore the connotation and characteristics of academic journals' discourse leading, the influence or contribution of social media discourse, news discourse, video discourse, policy discourse, peer review discourse and encyclopedia discourse on the citations decreases in turn.

This study is innovative from the academic journal level to analyze the deep relationships between altmetrics indicators and citations from the perspective of correlation. First, this paper explores the formation process of academic journals' discourse leading. Second, this paper integrates altmetrics indicators to study the correlation between discourse leading indicators and citations. This study will help to enrich and improve basic theoretical issues and indicators’ composition, provide theoretical support for the construction of the discourse leading evaluation system for academic journals and provide ideas for the evaluation practice activities.

This study aims to elucidate the dynamics of social media discourse during global health events, specifically investigating how users across different platforms perceive, react to and engage with information concerning such crises.

A mixed-method approach was employed, combining both quantitative and qualitative data collection. Initially, thematic analysis was applied to a data set of social media posts across four major platforms over a 12-month period. This was followed by sentiment analysis to discern the predominant emotions embedded within these communications. Statistical tools were used to validate findings, ensuring robustness in the results.

The results showcased discernible thematic and emotional disparities across platforms. While some platforms leaned toward factual information dissemination, others were rife with user sentiments, anecdotes and personal experiences. Overall, a global sense of concern was evident, but the ways in which this concern manifested varied significantly between platforms.

The primary limitation is the potential non-representativeness of the sample, as only four major social media platforms were considered. Future studies might expand the scope to include emerging platforms or non-English language platforms. Additionally, the rapidly evolving nature of social media discourse implies that findings might be time-bound, necessitating periodic follow-up studies.

Understanding the nature of discourse on various platforms can guide health organizations, policymakers and communicators in tailoring their messages. Recognizing where factual information is required, versus where sentiment and personal stories resonate, can enhance the efficacy of public health communication strategies.

The study underscores the societal reliance on social media for information during crises. Recognizing the different ways in which communities engage with, and are influenced by, platform-specific discourse can help in fostering a more informed and empathetic society, better equipped to handle global challenges.

This research is among the first to offer a comprehensive, cross-platform analysis of social media discourse during a global health event. By comparing user engagement across platforms, it provides unique insights into the multifaceted nature of public sentiment and information dissemination during crises.

This study seeks to explore the impact of “fear of missing out” (FOMO) and “psychological enhancement” (PE) on addiction to social media applications, subsequently influencing users' life satisfaction and continuous usage intention.

This research involved the administration of two sets of questionnaires during distinct periods: December 15 to December 30, 2022 and August 26 to September 2, 2023. The participants were college students from three universities in China, and the data collection utilized the “Questionnaire Star” platform. Only responses deemed valid and consistent were included in the subsequent statistical analysis. A total of 1,108 valid samples were used for the final analysis. Analyses including reliability, validity, path analysis, structural equation modeling, mediation effects and moderation effects were conducted using SPSS and AMOS software.

The study revealed that both FOMO and PE exerted positive influences on users' addiction to social media applications. Furthermore, this addiction was found to have a negative effect on users' life satisfaction while simultaneously contributing positively to their intention to continue using these platforms. The mediating effect of social media application addiction and the moderating impact of self-regulation were also substantiated through the analysis.

Firstly, it is important to note that the research population of this study is limited to college students, which may limit its generalizability and representativeness. Although college students are a group known for their familiarity with and frequent use of smartphones and social media apps, the findings may not fully capture the behaviors of social media app users in other age groups. To enhance the understanding of social media app addiction across different age groups, future studies should consider expanding the research population and conducting multi-group difference analyses. Secondly, while focusing on specific users within a particular region can minimize unexplained variance in model estimation, it may also restrict the broader applicability of the study results. Therefore, future studies should consider testing the research model with diverse groups from different regions and cultural backgrounds. This approach will provide valuable insights into how social media app addiction may vary across various contexts, thereby enriching our understanding of this phenomenon.

Our findings reveal that in the “attention economy” environment shaped by addiction, social media app managers should leverage technology to swiftly and accurately target audiences, attract them to their platforms and cultivate long-term relationships. Encouraging users to develop new beneficial habits through app-specific functions and precise services will foster continuous usage and unlock revenue and marketing opportunities for app companies.

Despite the extensive scholarly discourse on social media application addiction, there is a lack of a well-defined framework delineating how addictive user behaviors can be leveraged in the marketing strategies of social media application platforms. The present study seeks to address these gaps, contributing to a better understanding of the formation mechanisms and knowledge systems related to social media application addiction. By investigating the causes and consequences of such addiction, this research offers valuable insights and recommendations for the innovative development of these apps, given their widespread popularity. Concurrently, the study establishes a theoretical basis for the concept that users can mitigate the negative effects of social media addiction by exercising their own self-regulation.

As the functionalities and features of social media apps converge, their individual uniqueness starts to diminish, intensifying the competition among social media companies. This escalating rivalry places higher demands on these companies. This study aims to aid social media app companies in comprehending and analyzing the diverse psychological needs of users. By enriching their platform features and services, leading users towards addiction and gaining an edge in the “Attention Economy” competition. Understanding and catering to users' needs will be instrumental in thriving within this dynamic and evolving attention economy landscape.

Technological innovations provide huge opportunities to expand and revolutionize the scope of products and services offered. This is particularly true for tourism, which is undergoing significant changes due to the development of new technologies. The level of technology diffusion depends on several factors like the exchange of information among peers, and the attitude and shared perception among the contributors. The aim of the study is to explore the diffusion of technology in tourism with a specific focus on the social media discourse around new technologies. Thus, the paper investigates the level of interest in these new technologies analysing the information exchange occurring between individuals on Twitter in order to explore the influence of reciprocal networking.

To capture the attitudes expressed in the industry, the study analyses the ongoing discourse on Twitter as a proxy for the participants “interest in new technologies. Through a social network analysis of the tweets and retweets conducted over a period of nine months, the research maps the level of information exchange about the diffusion of new technologies. Moreover, the sentiment analysis provides an interesting overview of the individuals” attitudes towards the awareness or the adoption of new technologies.

Our analysis has provided several insights: (1) the information network on blockchain in tourism consists of participants who change very quickly over time (high turnover of accounts); (2) some contributors have an extremely important role in influencing the flow of information in the system (information centralization), they can have a generalist (discussing several topics) or a specialist (focusing on a specific topic) behaviour and this strategic choice influences their network's structure; (3) these central nodes also have an impact on the definition of positive and negative sentiment towards a topic (sentiment influencer).

The paper contributes to the literature on technology diffusion, by focusing on one of the preconditions of diffusion that is the shared positive attitude towards technological innovation. More specifically, we adopt a network-based approach, which is useful to explain the level of information exchange and the public discourse that can impact the shared perception and attitude towards technological innovation. The study also highlights the role of knowledge brokers in influencing this public discourse. Future studies can deepen the association between positive perception, higher levels of information exchange and increasing usage of specific technologies. Our results also suggest further exploring the opportunity to combine social media data and other sources of information to shed more light on the technological innovation diffusion processes.

This paper shows how practitioners can benefit from the analysis of information exchange about new technologies in tourism adopting a network perspective with the aim of understanding the level of influence among contributors. Moreover, the increasing interest in blockchain technology and the potential combination between social media data and other sources of information can offer promising insights.

The present study explores the level of technology diffusion through the analysis of information exchange on social media (Twitter). Furthermore, the dynamics of individual user behaviour offers a better understanding about media effects.

While previous research is focused on the users' perception towards the development of new technologies in tourism, the aim of this study is to investigate the dynamics behind the level of diffusion of information and awareness about these new technologies, which still represents an unexplored area of research.

This paper aims to analyze what Samarco and Brazilian magazines speak and say about Mariana’s environmental crime. Discover their doxa in this subject. Interpret the speakings, sayings and doxas through the theories of the treadmills of production, crime and law.

It is a qualitative and documental research and a narrative analysis. Regarding the documents: 45 were from public authorities, 14 from Samarco Mineração S.A. and 73 from Brazilian magazines. Theoretically, the authors resorted to Bourdieusian sociology (speaking, saying and doxa) and the treadmills of production, crime and law theories.

Samarco: speaking – mission statements; saying – detailed information and economic and financial concerns; doxa – assistance discourse. Brazilian magazines: speaking – external agents; saying – agreements; doxa – attribution, aggravations, historical facts, impacts and protests.

The absence of discussions that addressed this fatality, with its respective consequences, from an agenda that exposed and denounced how it exacerbated race, class and gender inequalities.

Regarding Mariana’s environmental crime: Samarco Mineração S.A. speaks and says through the treadmill of production theory and supports its doxa through the treadmill of crime theory, and Brazilian magazines speak and say through the treadmill of law theory and support their doxa through the treadmill of crime theory.

To provoke reflections on the relationship between the mining companies and the communities where they settle to develop their productive activities.

Concerning environmental crime in perspective, submit it to a theoretical interpretation based on sociological references, approach it in a debate linked to environmental criminology, and describe it through narratives exposed by the guilty company and by Brazilian magazines with high circulation.

People with pre-existing mental health conditions are more likely to be affected by global crises. The Covid-19 pandemic has presented them with unique challenges, including reduced contact with the psychiatric rehabilitation and support systems. Thus, understanding the emotional experience of this population may assist mental health organizations in future global crises.

In this paper, researchers analyzed the discourse of the mentally ill during the Covid-19 pandemic, as reflected in Israeli Facebook groups: three private groups and one public group. Researchers explored the language, reactions, emotions and sentiments used in these groups during the year before the pandemic, outbreak periods and remission periods, as well as the period before the vaccine’s introduction and after its appearance.

Analyzing groups’ discourse using the collective emotion theory suggests that the group that expressed the most significant difficulty was the Depression group, while individuals who suffer from social phobia/anxiety and PTSD were less affected during the lockdowns and restrictions forced by the outbreak.

Findings may serve as a tool for service providers during crises to monitor patients’ conditions, and assist individuals who need support and help.

The discourse on global value chains (GVC) is undergoing a transformation in terms of its conceptualisation, theorisation and pragmatic applications. Today, the production systems have become more complex as global economic order continues to witness marked geo-economic manoeuvring. Thus, the direction of discourse on GVC ought to move from mere theoretical propositions toward becoming more evidence based. There have been recent studies that have used the governance and upgrading propositions by Gary Gereffi and others to seek quantitative evidence. This study aims to decipher the quantitative discourse on GVC and to set the emerging and future research agenda.

Through a systematic literature review, the authors first analyse the quantitative studies on GVC carried out during the last two decades. The authors then outline a future research agenda and examine a few relevant modelling techniques that could potentially be used to solicit newer evidence in GVC research.

The authors categorise the quantitative discourse on GVC into three crucial themes, namely, GVC framework, GVC participation and position, environmental aspects and regionalisation in GVC. The most commonly used quantitative techniques are gravity model, panel data estimation, structural decomposition analysis and computable general equilibrium modelling.

This paper contributes to the GVC discourse in two ways. Firstly, the authors argue that the theoretical frameworks within the GVC discourse should be complemented by evidence-based quantitative studies. Secondly, the authors suggest potential modelling techniques that can be used on the emerging and future research agenda.

The contemporary business environment is characterised by an increasing reliance on artificial intelligence, automation, optimisation, efficient communication and data-driven decision making. Based on the limited academic literature that examines the managerial perspective on enterprise chatbots, the paper aims to explore organisational needs and expectations for enterprise chatbots from a managerial perspective, assesses the relationship between managerial knowledge and managerial opinion regarding enterprise chatbots, and delivers a framework for integrating chatbots into the digital workforce.

The paper presents a quantitative design. An online, self-administered survey yielded 111 valid responses from managers in service and manufacturing organisations based on convenience and snowball sampling strategies. Given the nature of the data and the research questions, the research was conducted using principal component analysis, parallel analysis, correlation, internal consistency and difference in means tests.

This research explores the managerial perspective on enterprise chatbots from multiple perspectives (i.e., adoption, suitability, development requirements, benefits, barriers, performance and implications), presents a heat map of the average level of chatbot need across industries and business units, highlights the urgent need for education and training initiatives targeted at decision makers, and provides a strategic framework for successful chatbot implementation.

This study equips managers and practitioners dealing with enterprise chatbots with knowledge to effectively leverage the expected benefits of investing in this technology for their organisations. It offers direction for developers in designing chatbots that align with organisational expectations, capabilities and skills.

Insights for managers, researchers and chatbot developers are provided. The work complements the few academic studies that examine enterprise chatbots from a managerial perspective and enriches related commercial studies with more rigourous statistical analysis. The paper contributes to the ongoing discourse on decision-making in the context of technology development, integration and education.

The advent of artificial intelligence (AI) in the accounting landscape marks a significant shift, promising gains in efficiency and accuracy but also eliciting concerns about job displacement (JD) and broader socio-economic implications. This study aims to provide an in-depth understanding of how AI’s integration in accounting contributes to JD, reshapes decision-making processes and reverberates across economic and social dimensions. It also offers evidence-based policy recommendations to mitigate adverse outcomes.

Leveraging a cross-sectional survey disseminated through Facebook, this research used snowball sampling to target a diverse cohort of accounting professionals. The collected data were subjected to meticulous analysis through descriptive and regression models, facilitated by SmartPLS 4 software.

The analysis revealed a significant correlation between AI’s increasing role in accounting and a heightened rate of JD. This study found that this displacement is not isolated; it has tangible repercussions on decision-making paradigms, economic well-being, professional work dynamics and social structures. These insights corroborate existing frameworks, including, but not limited to, theories of technological unemployment and behavioural adjustments.

Although providing valuable insights, this study acknowledges limitations such as the restricted sample size, the cross-sectional nature of the survey and the inherent biases of self-reported data. Future research could aim to extend these initial findings by adopting a longitudinal approach and potentially integrating external data sources.

As AI technology becomes increasingly ingrained in accounting practices, there is an urgent need for coordinated action among stakeholders. Policy recommendations include focused efforts on talent retention, investment in upskilling programs and the establishment of support mechanisms for those adversely affected by AI adoption.

By synthesising a range of theoretical perspectives, this study offers a comprehensive exploration of AI’s multi-dimensional impacts on the accounting profession. It stands out for its nuanced examination of JD and its economic and social implications, thereby contributing to both academic discourse and policy formulation. This work serves as an urgent call to action, highlighting the need for strategies that both exploit AI’s potential benefits and protect the workforce from its disruptive impact.