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Maneno mengi yanayohusu haki za binadamu na haki za kiteknolojia hayajatafsiriwa katika lugha ya Kiswahili. Kwa hivyo, wataalamu wa teknolojia na watetezi wa haki za kidijitali hutumia maneno ya Kiingereza – hata bila utohozi – wanapozungumzia haki za kiteknolojia. Hali hii ya mambo inachangia udhoofu fulani katika utetezi wa haki za kidijitali kwani wanaojaribu kueleza jamii umuhimu wa haki hizi hulazimishwa kutegemea msamiati wa Kiingereza usiyo na msingi au viungo na lugha ya Kiswahili Katika makala hii, tutazungumzia umuhimu wa kukaribisha watu kutumia lugha za Kiafrika kwenye mtandao.

Kiswahili ni lugha ya Kiafrika inayozungumzwa katika eneo zaidi sana duniani. Karibu watu milioni mia moja na arobaini Afrika mashariki wanazungumza Kiswahili kama lugha yao ya kwanza au ya pili, miongoni mwao Wakenya na Watanzania, wenyeji wa nchi ambamo Kiswahili ni lugha ya kitaifa. Tena kuna historia ndefu ya kutumiwa kwa lugha ya Kiswahili katika uandishi, uchapishaji na ubunifu wa utamaduni wa kisasa. Kiswahili pekee yake ndiyo lugha ya asili ya Kiafrika inayotumika kama lugha ya maalum ya Umoja wa Mataifa za Kiafrika. Hata hivyo, kwa upande wa matumizi ya Kiswahili, hasa kwenye mada ya teknolojia, Kiswahili imewachwa nyuma.

Zaidi ya maneno rasmi, uwepo wa lugha za Kiafrika ni muhimu kuimarisha jumuiya za Kiafrika mtandaoni kwani lugha inalenga sana haki na utambulisho wa watu. Miradi za kutafsiri maneno za kiteknolojia katika lugha ya Kiswahili inahimiza jumuiya za Afrika Mashariki kuunda jamii inayosimamia matakwa yao vyema. Makala hii basi inazingatia umuhimu wa lugha kwenye kuunda jamii na katika hatua za kuondoa mbinu za kikoloni mtandaoni ili wenyeji wa Afrika Mashariki wajione mtandaoni kwa ujumla wao wote. Makala pia itazingatia semiotiki ya lugha katika ubunifu wa teknolojia, na umuhimu wa kutafsiri jamii ya lugha ya Kiswahili katika harakati za kuondoa ukoloni katika ubunifu huu. Lakini sio tu kwamba lugha ya Kiswahili ndio pekee inayoweza kuondoa mbinu za kikoloni mtandaoni, kwani pia lugha hiyo ina ishara za kutawalwa kwa jamii fulani. Bali makala hii inatumia mfano wa Kiswahili kuhimiza utumiaji wa lugha za kiasili au za kimama mtandaoni ili kulinda mustakabali wa kidijitali wa umma.

Umuhimu wa makala hii ni kuashiria jipya umuhimu wa lugha katika harakati za kuendeleza haki za kidijitali na hasa kuondoa mbinu za kikoloni kwenye teknolojia, swala lisilowahijadiliwa katika lugha ya Kiswahili.

Retail investors are prone to be affected by information dissemination in social media with the rapid development of Web 2.0. The purpose of this study is to recognize the factors that may impact users' retweet behavior, namely information dissemination in the online financial community, through machine learning techniques.

This paper crawled data from the Chinese online financial community (Xueqiu.com) and extracted author-related, content-related, situation-related, stock-related and stock market-related features from the dataset. The best information dissemination prediction model based on these features was determined by evaluating five classifiers with various performance metrics, and the predictability of different feature groups was tested.

Five prevalent classifiers were evaluated with various performance metrics and the random forest classifier was proven to be the best retweet prediction model in the authors’ experiments. Moreover, the predictability of author-related, content-related and market-related features was illustrated to be relatively better than that of the other two feature groups. Several particularly important features, such as the author's followers and the rise and fall of the stock index, were recognized in this paper at last.

This study contributes to in-depth research on information dissemination in the financial domain. The findings of this study have important practical implications for government regulators to supervise public opinion in the financial market.

This paper aims to discuss Harymawan et al. (2023) and suggest a few areas for improvement.

This paper critically assesses Harymawan et al.’s (2023) position in the extant literature and discusses pertinent aspects.

This paper's primary focus is on Harymawan et al.’s (2023) conceptual development, especially chief executive officers' (CEOs) role in footnote disclosures.

This paper's viewpoints are relevant to readers interested in corporate textual disclosure and governance.

Online employee reviews have a substantial impact on employee recruitment, retention and the overall perception of a company’s image, making them a crucial element of its online reputation. Consequently, these reviews play a vital role in shaping the company’s competitiveness in the talent market. This study aims to investigate the role of employee loyalty in online reputation in the tourism and hospitality sector.

This study collected online reviews posted by 334,428 employees across 173 companies in the tourism and hospitality sector. Then, this study proposed a method for measuring employee loyalty toward the company through text comments. Furthermore, the role of employee loyalty in online reputation through regression models was analyzed.

Employee loyalty is positively associated with the closed-form evaluations, and the length and readability of open-ended comments is directly and positively associated with review helpfulness and is indirectly associated with review helpfulness through employee online reviews. Employees’ perception of job instability has a significant moderating effect on the above relationships.

This study contributes to the literature on loyalty in the tourism and hospitality industry, online reputation and employee risk perception. These findings offer a more profound understanding of the extra-role behaviors demonstrated by loyal employees, provide a theoretical foundation for the formation of a company’s online reputation and contribute to helping the tourism and service industry better address risk events. These conclusions provide valuable insights for companies in the fields of human resource management and online reputation management.

To the best of the authors’ knowledge, this study is the first to reveal the impact of employee loyalty on the company’s online reputation and provides important theoretical and practical implications for management.

Social media texts as a data source in depression research have emerged as a significant convergence between Information Management and Public Health in recent years. This paper aims to sort out the depression-related study conducted on the text on social media, with particular attention to the research theme and methods.

The authors finally selected research articles published in Web of Science, Wiley, ACM Digital Library, EBSCO, IEEE Xplore and JMIR databases, covering 57 articles.

(1) According to the coding results, Depression Prediction and Linguistic Characteristics and Information Behavior are the two most popular themes. The theme of Patient Needs has progressed over the past few years. Still, there is a lesser focus on Stigma and Antidepressants. (2) Researchers prefer quantitative methods such as machine learning and statistical analysis to qualitative ones. (4) According to the analysis of the data collection platforms, more researchers used comprehensive social media sites like Reddit and Facebook than depression-specific communities like Sunforum and Alonelylife.

The authors recommend employing machine learning and statistical analysis to explore factors related to Stigmatization and Antidepressants thoroughly. Additionally, conducting mixed-methods studies incorporating data from diverse sources would be valuable. Such approaches would provide insights beneficial to policymakers and pharmaceutical companies seeking a comprehensive understanding of depression.

This article signifies a pioneering effort in systematically gathering and examining the themes and methodologies within the intersection of health-related texts on social media and depression.

The need for infrastructure is growing as urbanization picks up speed, and the infrastructure REITs financing model has been crucial in reviving the vast infrastructure stock, alleviating the pressure on government funds and diversifying investment entities. This study aims to propose a framework to better assess the risks of infrastructure REITs, which can serve for the researchers and the policy makers to propose risk mitigation strategies and policy recommendations more purposively to facilitate successful implementation and long-term development of infrastructure REITs.

The infrastructure REITs risk evaluation index system is established through literature review and factor analysis, and the optimal comprehensive weight of the index is calculated using the combination weight. Then, a risk evaluation cloud model of infrastructure REITs is constructed, and experts quantify the qualitative language of infrastructure REITs risks. This paper verifies the feasibility and effectiveness of the model by taking a basic REITs project in China as an example. This paper takes infrastructure REITs project in China as an example, to verify the feasibility and effectiveness of the cloud evaluation method.

The research outcome shows that infrastructure REITs risks manifest in the risk of policy and legal, underlying asset, market, operational and credit. The main influencing factors in terms of their weights are tax policy risk, operation and management risk, liquidity risk, termination risk and default risk. The financing project is at a higher risk, and the probability of risk is 64.2%.

This research contributes to the existing body of knowledge by supplementing a set of scientific and practical risk evaluation methods to assess the potential risks of infrastructure REITs project, which contributes the infrastructure financing risk management system. Identify key risk factors for infrastructure REITs with underlying assets, which contributes to infrastructure REITs project management. This research can help relevant stakeholders to control risks throughout the infrastructure investment and financing life cycle, provide them with reference for investment and financing decision-making and promote more sustainable and healthy development of infrastructure REITs in developing countries.

The purpose of this paper is to investigate, from a thorough review of the literature, the role of metaverse-based quality 4.0 (MV-based Q4.0) in achieving manufacturing resilience (MFGRES). Based on a categorization of MV-based Q4.0 enabler technologies and MFGRES antecedents, the paper provides a conceptual framework depicting the relationship between both areas while exploring existing knowledge in current literature.

The paper is structured as a comprehensive systematic literature review (SLR) at the intersection of MV-based Q4.0 and MFGRES fields. From the Scopus database up to 2023, a final sample of 182 papers is selected based on the inclusion/exclusion criteria that shape the knowledge base of the research.

In light of the classification of reviewed papers, the findings show that artificial intelligence is especially well-suited to enhancing MFGRES. Transparency and flexibility are the resilience enablers that gain most from the implementation of MV-based Q4.0. Through analysis and synthesis of the literature, the study reveals the lack of an integrated approach combining both MV-based Q4.0 and MFGRES. This is particularly clear during disruptions.

This study has a significant impact on managers and businesses. It also advances knowledge of the importance of MV-based Q4.0 in achieving MFGRES and gaining its full rewards.

This paper makes significant recommendations for academics, particularly those who are interested in the metaverse concept within MFGRES. The study also helps managers by illuminating a key area to concentrate on for the improvement of MFGRES within their organizations. In light of this, future research directions are suggested.

The purpose of this study is to examine the relationship between positive emotion, self-efficacy, job satisfaction and turnover intention in the context of resource building during the socialization process of new faculty members, particularly in the context of the coronavirus disease 2019 (COVID-19) pandemic.

The study utilizes a quantitative research design and employs purposive sampling to obtain 554 valid questionnaires. The study analyzes the relationship between positive emotion, self-efficacy, job satisfaction and turnover intention and examines the influence of strategic human resource management (SHRM) on these variables.

The results of the study reveal that SHRM positively influences positive emotion and self-efficacy, which, in turn, positively impact job satisfaction. However, positive emotion is negatively related to turnover intention.

This study contributes to the existing literature on human resource management (HRM) by examining the impact of strategic HRM on the socialization process of new faculty members. The findings of the study have significant practical implications for the implementation of HRM in research-oriented universities.

Culture is considered a critical aspect of social media usage. The purpose of this paper is to explore how cultures and languages influence multilingual users' cross-cultural information sharing patterns.

This study used a crowdsourcing survey with Amazon Mechanical Turk to collect qualitative and quantitative data from 355 multilingual users who utilize two or more languages daily. A mixed-method approach combined statistical, and cluster analysis with thematic analysis was employed to analyze information sharing patterns among multilingual users in the Chinese cultural context.

It was found that most multilingual users surveyed preferred to share in their first and second language mainly because that is what others around them speak or use. Multilingual users have more diverse sharing characteristics and are more actively engaged in social media. The results also provide insights into what incentives make multilingual users engage in social media to share information related to Chinese culture with the MOA model. Finally, the ten motivation factors include learning, entertainment, empathy, personal gain, social engagement, altruism, self-expression, information, trust and sharing culture. One opportunity factor is identified, which is convenience. Three ability factors are recognized consist of self-efficacy, habit and personality.

The findings are conducive to promoting the active participation of multilingual users in online communities, increasing global resource sharing and information flow and promoting the consumption of digital cultural content.

This study is intended to investigate the relationship between supervisor bottom-line mentality (BLM) and employee workplace well-being. In addition, this study discusses the mediating roles of perception of organizational politics and job anxiety in this relationship.

Data were gathered from a two-wave survey of 301 full-time employees in southern China. The PROCESS macro in SPSS was applied to test the hypotheses.

Results showed that supervisor BLM was negatively related to employee workplace well-being. Moreover, perceptions of organizational politics and job anxiety played multiple mediating roles in the relationship between supervisor BLM and employee workplace well-being.

Drawing on the conservation of resource (COR) theory and cognitive-affective personality system (CAPS) theory, this study proposes a multiple mediation model to advance our understanding of how supervisor BLM affects employee workplace well-being.