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Digital teamwork has become prevalent and is ever since becoming part of the human work- and life-style, globally. But in comparison with face-to-face setting, virtual teams face multifold challenges. To date, scarce empirical research has examined whether team-breaking challenges are associated with limited access to peer nonverbal signals. This study examines whether access to body signals is associated with effective teamwork, and whether limited access provokes key team challenges. We also examine what social-psychological team concepts can be detected from peers' consciously or unconsciously displayed visual cues that cannot be as effectively gained without visual access. 14 dyadic teams of MBA students were examined in an online business negotiation task to reach an authentic commercial deal. Half of the teams negotiated only through voice and text, while the other half had camera access as well. Using an exploratory mixed methods analysis, we identified 12 unique team factors based on nonverbal data. We also found that teams with camera access could build mutual trust more rapidly, detect peer honesty better, and realize agreements on suggestions more accurately. Surprisingly, we also found instances where camera access became stressful and participants reported it as an additional burden. Conclusions and implications are reported at the end. [ABSTRACT FROM AUTHOR]

Digital marketing is one of the most important things that affect the targeted growth and development of e-businesses, digital marketing is essential for achieving business goals. Digital marketing has emerged as a powerful tool for businesses, enabling them to create brand awareness, build trust, and increase consumer awareness. This study aims to determine the influence of social media-based digital marketing on online businesses and impact of digital marketing (social media) on e-business growth. The role and applicability of social media on e-business growth is the main topic of this paper. This study aims to determine the influence of social media-based digital marketing on e-businesses and impact of digital marketing (social media) on business growth. The study paper's goal is to evaluate the efficacy of social media and digital media marketing techniques on e-business growth. The paper primarily examines the value of digital marketing as well as the impact of social media and technology tools on the efficacy of digital advertising strategies. In this paper, we bring a lot of information from different sources about digital marketing, where special importance is given to the impact of digital marketing on the growth of e-businesses. From the findings of this study, we came to the conclusion that digital marketing is necessary for a e-business, digital marketing affects the growth of a e-business and there are benefits of using digital marketing for e-business. Based on the fact that recently e-businesses have become very aware of investments in this field as any investment easily turns into profit, and based on the fact that digital marketing is the key to the success of business nowadays. The importance of this scientific research is that the knowledge gained from this work can be useful for another ebusinesses, how necessary is digital marketing for e-business, are they think that digital marketing affects the growth of a e-business, how aware they for the benefits of digital marketing for their e-business, what kind of digital marketing are they using for their e-business growth, digital marketing (social media) affects e-business growth. Also, it can be used to inspire those who have started their own e-business, showing you the role of digital marketing in your business. Numerous studies with results have been published on the relationships of personality factors with business intentions and business success. Also of particular importance in this research is the fact of how much an e-business can pay for digital marketing, to spend time or provide adequate staff for the realization of various advertisements, for the use of genuine marketing. [ABSTRACT FROM AUTHOR]

Reviews have a significant impact on online businesses. Nowadays, online consumers rely heavily on other people's reviews before purchasing a product, instead of looking at the product description. With the emergence of technology, malicious online actors are using techniques such as Natural Language Processing (NLP) and others to generate a large number of fake reviews to destroy their competitors' markets. To remedy this situation, several researches have been conducted in the last few years. Most of them have applied NLP techniques to preprocess the text before building Machine Learning (ML) or Deep Learning (DL) models to detect and filter these fake reviews. However, with the same NLP techniques, machine-generated fake reviews are increasing exponentially. This work explores a powerful text representation technique called Embedding models to combat the proliferation of fake reviews in online marketplaces. Indeed, these embedding structures can capture much more information from the data compared to other standard text representations. To do this, we tested our hypothesis in two different Recurrent Neural Network (RNN) architectures, namely Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), using fake review data from Amazon and TripAdvisor. Our experimental results show that our best-proposed model can distinguish between real and fake reviews with 91.44% accuracy. Furthermore, our results corroborate with the state-of-the-art research in this area and demonstrate some improvements over other approaches. Therefore, proper text representation improves the accuracy of fake review detection. [ABSTRACT FROM AUTHOR]

Although this book is situated within a US context, Ticona has done a good job in expounding the theoretical and empirical backdrops of her comparative research. Ticona, Julia Left to our own devices: coping with insecure work in a digital age. It is undoubtedly a relevant material for anyone interested in socio-digital inequalities, "the present" of work, as well as the possible future of work life with dignity, autonomy, and self-worth. [Extracted from the article]

Objective: The study aims to explore the journey of the development of an entrepreneurial mindset among Pakistani entrepreneurs. The continuous economic instability in the country has resulted in an unpredictable future and reduced job opportunities. Therefore, being and becoming an entrepreneur has gained great importance. The study used the self-narratives of twelve entrepreneurs. Research Design & Methods: This qualitative exploratory study utilized interpretivism as a research paradigm. Using the grounded theory approach, this study employed content analysis to analyze qualitative data. Interviews were conducted to collect data, which was subsequently transcribed, coded, and analyzed before developing the themes. Findings: The research revealed that entrepreneurship is a mindset, not an occupation or business. Entrepreneurs must be agile, knowledgeable, capable of learning, and have analyzing powers to take a risk. Social networking and online business make the business substantial. Furthermore, successful business stories inspire people to start their businesses. Implications & Recommendations: The findings of this study are valuable for young people and entrepreneurs who are inclined towards starting a business rather than pursuing a job, which has become more difficult, competitive, and restrictive in terms of income opportunities and the application of innovative ideas. Moreover, government institutions and policymakers can formulate policies to increase entrepreneurial activities based on the research findings. Contribution & Value Added: This could be one of the first studies conducted in Pakistan to identify the elements that lead to the formation of an entrepreneurial mindset, and themes obtained from the research can be utilized for the benefit of entrepreneurial development. Existing research gaps were filled by the contribution of this study. In addition, this study provides practical insights to being and becoming entrepreneurs. [ABSTRACT FROM AUTHOR]

In Facebook Inc v Australian Information Commissioner, the High Court of Australia will consider whether the American parent company behind the social media platform is amenable to the Federal Court of Australia's jurisdiction in proceedings brought in the wake of the Cambridge Analytica data privacy scandal. The central issue is whether Facebook Inc 'carries on business' in Australia so as to be within the extraterritorial reach of the Privacy Act 1988 (Cth). I argue that it does. Although traditional indicia for 'carrying on a business' may be absent in Facebook Inc's operations as relevant to this case, the assessment should be approached having regard to the limitations of territorial thinking for analysis of digital subject matter. A purposive construction of the Privacy Act favours this analysis. I argue that the Federal Court was warranted in finding that the Commissioner had established a prima facie case sufficient to justify the Court's exercise of its long-arm jurisdiction. [ABSTRACT FROM AUTHOR]

The Online business area in India has developed at a momentous speed of 34% Compounded Annual Growth Rate (CAGR) beginning around 2009 and is assessed to develop at a CAGR of 63% to arrive at USD 8.5 billion in CY 2016. Nonetheless, similar to any remaining prospering areas, there are difficulties tormenting this area also, one of which is insufficient and wasteful legitimate and administrative structure ready to adapt to guaranteeing freedoms and commitments of the contracting parties. India established the Information Technology Act in June 2000. Yet, this is being an empowering resolution in particular; we want more guidelines for making Web based business exchanges more pleasant and accomplishing a more purchaser accommodating Internet business climate in India. This paper tries to concentrate on the current Web based business regulations and guidelines in India, their viability in managing the lawful issues of Internet business and any requirement for additional option in the equivalent. [ABSTRACT FROM AUTHOR]

This Article develops the five-element HAPPY model to study Chinese regulation: the regulatory process is hierarchical, the top leadership is adaptable, the Chinese regulators are parochial, the firms are pliant and the Chinese public need to yelp to be heard. By focusing on China’s great reversal in regulating the platform economy, I show that Chinese policy volatilities have stemmed from the hierarchical structure in which power is centralized among top leaders, who also suffer from a chronic deficit of information. I particularly highlight how favorable support from the top leadership, aggressive lobbying from tech firms, and the bureaucratic inertia of the regulators together contributed to a lag in regulating Chinese online platforms. When a crisis looms, the top leadership quickly mobilizes all administrative resources and propaganda to initiate a law enforcement campaign against tech giants. However, without strong judicial oversight, aggressive agency interventions create the risk of over-enforcement and administrative abuse. Thus far, China’s reorientation of its policy control has significantly bolstered its regulatory capacity across various fronts including financial, antitrust, and data regulation. By exerting greater oversight over platform governance, the government has enhanced the bargaining power of the various platform participants in dealing with the platforms. The government’s heavy-handed approach has also afforded it great leverage to nudge tech firms to prioritize developing cutting-edge technologies, and to steer them away from foreign stock markets, thus reducing reliance on the West for both technologies and capital. Despite the campaign’s immediate impact, it remains to be seen whether it will bring about lasting changes, especially in light of the persistent lobbying from tech firms and the risk of regulatory capture. At the same time, the volatile policy swing has itself generated risks and uncertainties, which in turn could cause turmoil to domestic social and financial stability. As the rest of the world is similarly confronted with thorny questions about how to rein in Big Tech, China’s experience with platform regulation could offer some lessons that inform the global policy debate. Although this Article focuses primarily on the platform economy, the HAPPY model has the promise to shed light on the complexity and dynamics in other areas of regulatory governance in China and beyond. [ABSTRACT FROM AUTHOR]

The aim of the paper is to investigate the impact of SEO on the business performance of a private university in Sarajevo. Thus, the main research question provides the finding on how does the implementation of SEO influence the performance of business. Moreover, the tested hypothesis presents weather SEO positively influence business performance of International Burch University (IBU). The research strategy is to analyze primary data derived from a case study, which is generated following a conversation with the Head of IBU Marketing and PR team. Data sample is derived from Google Analytics (focusing on number of visits and sessions, average engagement time, keywords and SERP positioning). Seobility tools are employed in data analysis. Business performance is calculated through IBU CRM system, focusing on student enrolment. Findings indicate that increasing a site's rankings on search engine results pages (SERPs) led to a variety of positive outcomes for companies including an increase in the number of visitors to the site, an increase in the average amount of time users spent on the site, increased user engagement, and an increase in student enrollment, which resulted in IBU increased annual sales revenue. It will benefit many different groups, including the government, which will benefit in both microeconomic and macroeconomic senses, digital marketing enthusiasts and SEO experts, and the academic world, which will benefit as a framework for future studies and research in the field of SEO recognition and implementation in business queries. [ABSTRACT FROM AUTHOR]

This article explains the main mechanisms influencing the knowledge collaboration dynamics occurring across an online business community. Prior research study had conceived firms as autonomous entities competing against each other to reach the competitive advantage. Nonetheless, online business social networks (BSNs) can be seen as networks of organizations that interact within digital structures, providing an optimal locus to foster external knowledge flows, enabling participants to share knowledge across organizational boundaries, and eventually leading to open innovation outcomes. We analyze how virtual networks of business relationships influence the form of knowledge collaboration firms can be engaged in. We analyze the entire three-year collaborative history of a BSN. After a promising launch of the BSN, it declined and failed. By analyzing front- and backstage combined with organizational and technological features of the online business community, we identify and discuss five categories of mechanisms affecting the knowledge collaboration over time and reducing the firms’ uncertainty in exchanging information: first, orchestrators’ skills and competencies in running the online platform; second, internal firm capabilities allocating proper organizational resources; third, usability of the digital platform; four, interconnections between frontstage and backstage combined with technological and organizational features; and fifth, perceived virtual copresence. [ABSTRACT FROM AUTHOR]

The article focuses on the federal statute known as Section 230, which protects online companies from being held accountable for content created by users. It mentions that to foster innovation in the marketplace of ideas, reduce obstacles for startups, and hinder more significant government authority over the internet, it is essential to retain its extensive safeguards.

The changes in our daily lives, or, which have been called the "new normal," have an implication in the shifting of tradition to online business activities. This study aims to explore how effective search engine marketing, content marketing, influential marketing, social media marketing, and email marketing as strategies in digital marketing used by different MSMEs operating in NCR under the new normal and if these strategies can give a long-term gain in businesses. The study was conducted through a survey questionnaire by MSMEs owners in NCR. The study results found that Social Media Marketing is very effective as a Digital Marketing strategy and has a significantly low positive relationship with Digital Content and Influencer Marketing. The study will contribute to identifying the effectiveness of digital marketing strategies that will benefit the businesses under the new normal in terms of increasing their sales and in the future, as people get accustomed to the activities under the new normal. [ABSTRACT FROM AUTHOR]

Copyright of Proceedings of the Faculty of Economics & Business in Zagreb / Zbornik Ekonomskog Fakulteta u Zagrebu is the property of Ekonomski Fakultet u Zagrebu and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Corporate blogs are expected to facilitate communication, knowledge sharing, and collaborative innovation within organizations. However, empirical evidence has yet to be found illustrating whether and how such applications have affected job performance. Drawing upon social network theory, we postulate a conceptual model suggesting that employees’ online social relationships accumulated through work- and nonwork-related blog participation will engender different effects on job performance. The model is empirically tested using digital trace and archival data collected from two in-practice systems of a large telecommunications company. The results reveal that, in the work-related blog network, the structural and cognitive dimensions of social relationships positively affect job performance, whereas the relational dimension shows a negative influence. Meanwhile, participation in nonwork-related blog network benefits job performance for employees with a high level of performance in the previous time period, but is detrimental for other employees. The findings uncover the influencing mechanism of corporate blogging on job performance and offer practical advice for managers to better exploit the value of intraorganizational social media. [ABSTRACT FROM PUBLISHER]

Online professional networks are important tools used by recruiters to find qualified candidates for job openings. Within these networks, professional recommendations are used to supplement profiles and add credibility. These recommendations tend to be overly positive, full of superlatives, and lacking in critical statements (referred to as scope of improvement). We draw on the theory of online trust to argue that having scope of improvement and superlatives may affect various dimensions of trust and to show how online trust, in turn, can affect the usefulness of a recommendation and the likelihood of receiving an interview. We contribute to the body of work on online trust both theoretically and empirically. From a theory perspective, we explain why including scope of improvement and superlatives in recommendations on online professional networks may help certain candidates in getting an interview but hurt others. From an empirical perspective, we provide a unique empirical setting that allows us to observe not only the effect of scope of improvement and superlatives, but also validate the theoretically argued underlying process. Furthermore, through discussion with recruiters, we identify then test contextual factors that differentiate recommendations on online professional networks from traditional recommendations. In this study, we use a scenario-based, quasiexperimental survey to test the effects of superlatives and scope of improvement on the usefulness and effectiveness of recommendations. Further, we test the mediating role of trust and how the experience levels of the recommendee affect the sign and strength of these relationships. Our findings indicate that including scope of improvement increases the effectiveness and usefulness of recommendations for candidates at low- and middle levels of experience. For the most experienced candidates, including scope of improvement has a negative effect on effectiveness. Superlatives negatively affect the perceived competence of the recommender and thus should be avoided. This negative effect is reduced when combined with scope of improvement. [ABSTRACT FROM AUTHOR]

The article offers information on how the respective beneficiary can secure his income from the business model for as long as possible along with a value chain of digital business models. Topics include contractual license cannot replace an absolute right especially not to third parties, & bilateral relationship limits the freedom to exploit the data.

Professional networks are vital for individuals' career advancement. Research demonstrates, however, that women are often disadvantaged in their access to such networks. Using a randomized field experiment at an IT conference, we found that women had worse networking outcomes than men. Relative to men, women met 42% fewer new contacts, spent 48% less time talking to them, and added 25% fewer LinkedIn connections. We theorize that in fields where women are underrepresented (e.g., IT) two networking barriers--search and social--differentially affect men and women. We designed and experimentally tested interventions for reducing these barriers. The search intervention was designed to facilitate locating diverse contacts and information. The social intervention was designed to facilitate helping behavior and connecting across social boundaries. Our findings indicate that the search intervention increased the number of new contacts women met by 57%, the time they spent talking with them by 90%, the number of LinkedIn connections they added by 29%, and their odds of changing jobs by a factor of 1.6. The social intervention also increased the time women spent talking to new contacts by 66%. However, the interventions did not improve men's outcomes. Our results show that simple interventions can help women expand their networks and find jobs. [ABSTRACT FROM AUTHOR]

Today, online shopping is a great innovation, making life easier and more convenient for everyone. The study aimed to determine the factors affecting the level of consumer satisfaction of online businesses. ffis research study used ffomassen's model that allows the researcher to determine the factors that affect the customers' satisfaction and what factors greatly inffuence their satisfaction. Five factors contributed to this research study: fast transaction, mode of payment convenience, price and values, customer service, and product quality. ffis research used a descriptive survey meffod of distributing questionnaires to 393 respondents. Questionnaires were distributed among all online consumers in the selected eleven barangays in Nasipit, Agusan del Norte. Based on the ffndings, there is no signiffcant difference in the online business level of consumer satisfaction as to their proffle. The factor that greatly affects consumer satisfaction of online business is fast transaction resulted in highly satisfied. It was recommended that online sellers continue and maintain their fast transactions and ffnd more ways to improve their payment system to pay easily and conveniently. [ABSTRACT FROM AUTHOR]

The use of simulations is prevalent across business schools in colleges and universities. Research has shown that they can be useful in bridging theory with practice and preparing students for "real world" employment. However, there is limited research on determining the best pedagogical approaches for using these tools in a classroom setting. In this study, two approaches to using the Capsim "Capstone" online business strategy software are explored and measured for overall effectiveness and meeting learning outcomes. Results show that the pedagogical approach matters less in determining learning success as compared to other variables including average team logins, individual login behavior, experience of the instructor in using the simulation, and the simulation industry environment itself (i.e., number of studentrun teams versus number of computer-run teams). The results have implications for the delivery of computer simulations in class as well as their use as part of a course grade. [ABSTRACT FROM AUTHOR]

The article presents overview on regulation of digital business models in Medienstaatsvertrag (New State Media Treaty or MStV). Topics include the federal states began to renew the broadcasting regime and to adapt it comprehensively to the digital media; and media intermediaries and video sharing services in the focus of media law regulation on social networks, user-generated content portals, blogging portals, and search engines.

In the fashion and retail industry, a group of startups, referred to as Direct-to-Consumer (DTC) brands, are proliferating. DTC brands are defined as e-commerce brands that sell directly to consumers, without retailer 'middlemen' like department stores. They typically begin as a purely online business, fully leveraging digital channels for marketing and selling. Given the limited research on the topic, this paper aims to identify determinants of consumers' attitudes and re-purchase intentions toward DTC brands. The initial qualitative phase of in-depth interviews with frequent DTC shoppers, resulted in the identification of eight determinants. The subsequent quantitative analysis with 210 US DTC shoppers confirmed that co-creation, cost-effectiveness, website attractiveness, brand uniqueness, social media engagement, and innovativeness of DTC brands significantly influence consumers' attitudes while cost-effectiveness (indirectly), brand uniqueness, social media engagement, and brand innovativeness affect consumers re-purchase intentions. The findings offer insights for aspiring entrepreneurs and incumbent retailers on strengthening their value propositions. [ABSTRACT FROM AUTHOR]

This paper provides preliminary evidence on accountants' low engagement with Social Networking technologies (SNT) in companies operating in the United Arab Emirates (UAE). SNT are credited with potentials for adding business value and are touted as a new wave of technologies for creating, sharing and communicating information that was previously difficult to achieve in the workplace. The paper draws attention to the importance of understanding the communicative ecology within which SNT are adopted. Using a qualitative methodology in tune with the social, technical, and discursive features, the paper emphasizes the importance of understanding the uptake of SNT in organizations in relation to different professionals' communicative ecologies. Given the growing scholarly interest in the new avenues opened up by SNT for communication in accounting and related exchange of information, the paper focuses on studying accountants' communicative ecology. The paper reports the findings of twenty interviews with accountants and finance managers in five companies located in Dubai and discusses the difficulties they experience in integrating SNT into their professional ecology. The paper concludes that the realization of SNT potentials to add business value requires a much more complex structural reform and needs to be carefully managed if it is to create business value. It suggests that considering the communicative ecology underpinning accountants' practice is essential for ensuring effective communication and successful technology implementation. Our findings challenged the overenthusiastic speculation about the prescribed promises and benefits of these new technologies and draw attention to the relationship between SNT communication and collaboration opportunities and the 'communicative ecology' underpinning their use. The findings herein should be of help for those considering the adoption and investment in SNT in business organizations. It draws attention to the importance of embracing a broader perspective that accounts for the various layers constituting the communicative ecology of the different professional groups. [ABSTRACT FROM AUTHOR]

Nowadays, product placements are commonly presented on mobile social media but related studies are rare. The main purpose of the study is to investigate the effects of content likeability, content credibility, and social media engagement on users' acceptance of product placement in mobile social networks. The results of the online survey indicate that content likeability is an antecedent of social media engagement and content credibility; social media engagement has an influence on content credibility; and content likeability, content credibility, and social media engagement both directly affect user acceptance of product placement in mobile social networks. Furthermore, social media engagement has an interaction effect with content likeability on the content credibility of mobile social networks. The results of the multi-group analysis indicate that young adults show differences with middle-aged adults in the direct effect of content likeability on social media engagement and in the interaction effect of content credibility and social media engagement on the acceptance of product placement in mobile social networks. The implications for practitioners are discussed on the basis of the empirical findings. [ABSTRACT FROM AUTHOR]

With the prosperity of the location-based social networks, next point-of-interest (POI) recommendation has become an increasingly significant requirement since it can benefit both users and business. Obtaining insight into user mobility for the next POI recommendations is a vital yet challenging task. Existing approaches to understanding user mobility mainly gloss over the check-in sequence, making it fail to explicitly capture the subtle POI–POI interactions across the entire user check-in history and distinguish relevant check-ins from the irrelevant. In this paper, we proposed a novel recommendation approach, namely geographical-temporal awareness hierarchical attention network (GT-HAN) to resolve those issues. We first establish a geographical-temporal attention network to simultaneously uncover the overall sequence dependence and the subtle POI–POI relationships. Then, a context-specific co-attention network was designed to learn to change user preferences by adaptively selecting relevant check-in activities from check-in histories, which enabled GT-HAN to distinguish degrees of user preference for different check-ins. Finally, we make a POI recommendation using a conditional probability distribution function. Experimental results on real world datasets (obtained from Foursquare and Gowalla) show that the GT-HAN model significantly outperforms current state-of-the-art approaches, and demonstrating the benefits produced by new technologies incorporated into GT-HAN. [ABSTRACT FROM AUTHOR]

Cross-site account correlation correlates users who have multiple accounts but the same identity across online social networks (OSNs). Being able to identify cross-site users is important for a variety of applications in social networks, security, and electronic commerce, such as social link prediction and cross-domain recommendation. Because of either heterogeneous characteristics of platforms or some unobserved but intrinsic individual factors, the same individuals are likely to behave differently across OSNs, which accordingly causes many challenges for correlating accounts. Traditionally, account correlation is measured by analyzing user-generated content, such as writing style, rules of naming user accounts, or some existing metadata (e.g., account profile, account historical activities). Accounts can be correlated by de-anonymizing user behaviors, which is sometimes infeasible since such data are not often available. In this work, we propose a method, called ACCount eMbedding (ACCM), to go beyond text data and leverage semantics of network structures, a possibility that has not been well explored so far. ACCM aims to correlate accounts with high accuracy by exploiting the semantic information among accounts through random walks. It models and understands latent representations of accounts using an embedding framework similar to sequences of words in natural language models. It also learns a transformation matrix to project node representations into a common dimensional space for comparison. With evaluations on both real-world and synthetic data sets, we empirically demonstrate that ACCM provides performance improvement compared with several state-of-the-art baselines in correlating user accounts between OSNs. [ABSTRACT FROM AUTHOR]

There is an increased demand for a skilled workforce that is prepared for work in today's digital economy, which is often done in virtual teams. Thus, while many students today have little or no experience working in this mode, they are often placed in virtual teams early in their careers. We argue that that if students have the opportunity to acquire virtual leadership skills in an authentic setting in their undergraduate program, they will be more prepared when they are placed in virtual teams and virtual leadership roles in the workplace. An instructional strategy was implemented in a large online undergraduate business course to provide students with the experience of working in virtual teams in an authentic setting and the findings of the study highlight the importance of organization, technology management, communication, managing student perceptions, and coaching when using this strategy to teach virtual leadership and virtual team skills. [ABSTRACT FROM AUTHOR]

People use various online social networks for different purposes. The user information on each social network is usually partial. Thus, matching the users across these multiple online social networks is of great significance for providing new services as well as new insights on user behaviors. Recent research shows that group structure widely exists on social networks, in which members work together with certain purpose and are more influential than individuals on online social networks. Previous works provide outstanding solutions for mapping individuals, but few ones pay attention to the study of groups across multiple social networks. To address the research gap, we first aim to propose an effective method to detect similar group across multiple social networks. The method mainly has three steps, including detecting group structure based on random walks, extracting similarity features, and inferring group similarity using probabilistic graphical model. We evaluate our algorithm on five different types of online social networks. Experimental results show that our method achieves 0.693, 0.779, 0.729 in precision, recall, and ${F}1$ -measure, which significantly surpass the state-of-the-art by 31.4%–44.3%, 17.3%–26.3%, and 25.9%–31.6%, respectively. The outstanding performance of our method demonstrates that our proposal can reach the requirement of detecting similar groups across social networks. In particular, the result of this paper paves the way for the recommendation system, link prediction and information diffusion across sites. [ABSTRACT FROM AUTHOR]

The impacts of digital technology on the spaces and practices of firms are of increasing concern, yet we know comparatively little about how emerging digital business models affect the 'business spaces' of service firms. We draw on case study research within five leading online fashion retailers to identify interweaving virtual and physical spaces of online retailing that are expressed through intra - and inter-firm digital interdependency management. This allows us to build a conceptualisation of the 'business code/spaces' of digital service firms, i.e., the entanglements between virtual, information-rich and responsive networked infrastructures, and materially and socially situated infrastructures. The conceptualisation of 'business code/spaces' reveals how combinations of embedded interpersonal decision-making within office-based work communities, networked partners, their established processes and bureaucracies, as well as the physical restrictions of space and place together reproduce spatial fixes and local–global geographies, but in ways fundamentally defined by digital technologies and business models. Our conceptualisation of 'business code/spaces', therefore, contributes to research examining the inter-relationships between 'the digital' and business practices as well as work concerning global retailing. [ABSTRACT FROM AUTHOR]

The study explores whether the penetration, explicitness, and symbolic corporate social responsibility (CSR) communication practices of organizations are associated with the characteristics of the countries to which they belong. By focusing on the national business systems (NBSs) of Asian countries, the study analyzes the websites of companies based in Japan, the Republic of Korea, Mainland China, and Hong Kong, to address strategic‐operational (penetration), discretionary‐non‐discretionary (explicitness), and substantial‐symbolic (symbolic practices) dimensions of CSR communication. The findings suggest that online CSR communication in Asian mirrors national business profiles. In particular, CSR penetration and explicitness in companies located in different Asian countries vary, whereas CSR symbolic communication does not appear to be related to the specifics of each NBS. The research extends the understanding of CSR communication in Asia based on the NBS theory. The findings can indicate to Asian managers how they can make CSR communication more effective, in terms of penetration and explicitness, and how to avoid symbolic CSR practices. [ABSTRACT FROM AUTHOR]

The use of social network sites helps people to make and maintain social ties accumulating social capital, which is increasingly important for individual success. There is a wide variation in the amount and structure of online ties, and to some extent this variation is contingent on specific online user behaviors which are to date under-researched. In this work, we examine an entire city-bounded friendship network (N = 194,601) extracted from VK social network site to explore how specific online user behaviors are related to structural social capital in a network of geographically proximate ties. Social network analysis was used to evaluate individual social capital as a network asset, and multiple regression analysis–to determine and estimate the effects of online user behaviors on social capital. The analysis reveals that the graph is both clustered and highly centralized which suggests the presence of a hierarchical structure: a set of sub-communities united by city-level hubs. Against this background, membership in more online groups is positively associated with user's brokerage in the location-bounded network. Additionally, the share of local friends, the number of received likes and the duration of SNS use are associated with social capital indicators. This contributes to the literature on the formation of online social capital, examined at the level of a large and geographically localized population. [ABSTRACT FROM AUTHOR]

In recent years, due to the booming development of online social networks, fake news has been appearing in large numbers and widespread in the online world. With deceptive words, online social network users can get infected by these online fake news easily, which has brought about tremendous effects on the offline society already. An important goal in improving the trustworthiness of information in online social networks is to identify the fake news timely. However, fake news detection remains to be a challenge, primarily because the content is crafted to resemble the truth in order to deceive readers, and without fact-checking or additional information, it is often hard to determine veracity by text analysis alone. In this paper, we first proposed multi-level convolutional neural network (MCNN), which introduced the local convolutional features as well as the global semantics features, to effectively capture semantic information from article texts which can be used to classify the news as fake or not. We then employed a method of calculating the weight of sensitive words (TFW), which has shown their stronger importance with their fake or true labels. Finally, we develop MCNN-TFW, a multiple-level convolutional neural network-based fake news detection system, which is combined to perform fake news detection in that MCNN extracts article representation and WS calculates the weight of sensitive words for each news. Extensive experiments have been done on fake news detection in cultural communication to compare MCNN-TFW with several state-of-the-art models, and the experimental results have demonstrated the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

During the last few years online-only media have been explored as an alternative to mainstream media. The development of this new media model coincides in time with an increase in dependence on social networks. Online media editors estimate that one third of their visits proceed from Facebook, a figure that obliges them to create specific strategies to ensure their company's reputation and growth in the 2.0 field. The aim of this article is to assess what motivates Spanish digitalnative newspapers to act on social networks, analyse their internal view of these channels, and describe their strategies for managing their relationship with audiences. Based on a qualitative and longitudinal approach, we conducted in-depth interviews with the social media editors of the most relevant digital-native newspapers in Spain--El Confidencial, Eldiario.es, El Español and El HuffPost--during 2017 and 2019, in order to trace the evolution of their professional routines. These social media editors consider that although digital-native newsrooms are smaller than traditional ones, they are more agile in reacting to metrics. Our results also confirm that Instagram is generating great expectations, and the new paywall system is affecting the way audiences are understood. [ABSTRACT FROM AUTHOR]

News and media web pages generate valuable consumer data, collected by third-party servers. Using longitudinal experiments, this article shows that third-party servers are active in 34 cases of European public service media (PSM) websites from 19 countries. This constitutes a pressing privacy problem in relation to GDPR and challenges the notion of PSM organizations as particularly trusted providers of media content. This has implications for their role and placement in the commercial media landscape as well as for their independency, but also for their survival in the future media landscape. Our analysis shows not only connections between the presence of advertisement and the number of third-party servers found but also a reflection of different types of European media systems. To provide a benchmark for our analysis, we also analysed 64 private media websites for the presence of third-party servers. The empirical results suggest a pressing need for discussions on whether and how PSM organizations can participate in the commercial web ecology of user data exchange and utilization, for example, for the purposes of user profiling, targeting and PSM performance measurement. [ABSTRACT FROM AUTHOR]

The key to discover potential opportunity information in cross-organisation business processes (COBPs) is to identify the primary roles and actors, i.e. how to obtain their associations according to the interactive behaviours within the complex social networks. The information of roles in COBPs is commonly considered important and explicitly related with activities contained in COBPs. In this paper, we define a role as a configurable resource model integrating the capabilities and knowledge required to the qualified actors. Furthermore, we introduce two networks named as role-based interactive behaviour network and handover of work social network to investigate the information on roles. How to build the complex social network mapped on roles from COBPs is also discussed, and an approach to obtain the potential opportunity information is proposed by combining with the significance of roles and actors. The simulation result shows that the primary roles may not completely correspond to the central position in networks, but they are closely associated with more reliable actors. [ABSTRACT FROM AUTHOR]

Because of Wuhan 2019 Novel Coronavirus (2019-nCoV) outbreak around the world, global trade and supply chains have been interrupted by the uncertainties of this unexpected event. In this unexpected event, it is important for the customers and businesses to make right decisions at the right time. Social networking sites have become important for information sharing and online business effectiveness and played important roles in this unexpected event for the customers and businesses to make right decisions with limited information. They can be a good choice to share information in real-time as they are recognized as a significant tool for public health and economy development. This work highlights the impact of Coronavirus outbreak on the global economy and the role of social network sites in sharing the customers' and businesses' information and concerns about the Coronavirus outbreak. The paper concludes with some examples of travelers' concerns along with their feedback in social networking sites and recommendation for the future works. [ABSTRACT FROM AUTHOR]

We consider a predator-prey relationship in a fair system in which interacting species have different needs of resources to survive. We analyzed qualitatively the outcome of interaction using a modified logistic predator-prey model with Allee threshold in both predator and prey equations. We showed that the system had very rich dynamical behavior as stability around fixed points and periodic solutions could be obtained at certain conditions. Interaction outcome is highly submitted to initial conditions, species behavior, and the threshold applied. Numerical results suggested adapting resource allocation and the threshold value to optimize ecosystem sustainability. [ABSTRACT FROM AUTHOR]

The growing interest in classroom peer feedback has provided the academic community with the possibility of developing corporate employees' writing skills through the interaction of peer feedback. The present study aims to investigate the types and the influence of peer feedback in collaborative revision in blended learning for developing corporate employees' business writing. As the participants, the four managers of a Korea-based airline company participated in the present case study. During the collaborative revision in blended learning, the participants' spoken comments for the offline peer feedback and the written comments for the online peer feedback were collected and analyzed. The findings reveal that offline peer feedback helped the participants generate ideas and gather information. Meanwhile, online peer feedback helped them correct their writing appropriately. Conclusively, both offline and online peer feedback in collaborative revision in blended learning appear to have had a positive influence on developing the participants' business writing. For future research, the investigative interest might need to be drawn to the relationship between the types of peer feedback and the rhetorical function for developing corporate employees' business writing. [ABSTRACT FROM AUTHOR]

• Twitter data is a source of information to analyse marijuana prevalence. • A model for marijuana use surveillance to get information fusion to support policymakers. • Social network and opinion mining to analyse the population thoughts about marijuana. The impact that connected community have on precision health or medicine and vice versa offers opportunities for any type of research and survey information, e. g, to predict trends in health-related issues, specifically people behavior towards drug use. Here, precision medicine influences the way to treat the information and get a better outcome to support the stakeholder decision. Online social networks analysis seems to be good tools to quickly monitor the population behavior where users freely share large amounts of information related to their own lives on day- to- day basis. This novel kind of data can be used to get additional real time insights from people to understand their actual behavior related to drug use (Cortés et al., 2017). The aim of this research is to generated an information fusion model of marijuana use tendency confident enough to be employed by stakeholders. So, we will: (a) collect and process the data from Twitter; (b) design a set of algorithms to estimate the tendency of marijuana use in relation to age, localization and gender, moreover, used a set of processes and activities to verify if our model were performing as expected; and (c) fusion of the information in a model to fully characterize the marijuana use population comparable to the national marijuana consume survey for policy makers utilization to improve drug use prevention. First,we collect the data from Twitter accounts based in Chile using an algorithm for traversing graph data structures, we collected the data from Twitter accounts based in Chile. Then, we estimated marijuana user prevalence during a period from 2006 to 2018 and, within each of the years we predicted the prevalence of user population in relation with age (in range), the localization (regions) and gender. Finally, we built indicators to explore the similarity between data obtained through Twitter (our results) and the actual data collected by the National Service for the Prevention and Rehabilitation of Drug and Alcohol (SENDA) under the same variables analyze in their own survey. When we compare the results of the algorithms and methods developed by us with those provided by the SENDA, we observed that most of the indicators present similar trends, i.e., the variation of the prevalence by years in the age, location and gender, showed similar changes in both analyzes. Also, the algorithms effectiveness and capacity to predict variations of complex cases like marijuana use in Chilean population. This study is a key opportunity to obtain in a faster, low cost and continuous way information about marijuana use, also, is an excellent tool for marijuana surveillance to get information to support policy makers and stakeholder decisions. [ABSTRACT FROM AUTHOR]

User tags in social network are valuable information for many applications such as Web search, recommender systems and online advertising. Thus, extracting high quality tags to capture user interest has attracted many researchers' study in recent years. Most previous studies inferred users' interest based on text posted in social network. In some cases, ordinary users usually only publish a small number of text posts and text information is not related to their interest very much. Compared with famous user, it is more challenging to find non-famous (ordinary) user's interest. In this paper, we propose a probabilistic topic model, Bi-Labeled LDA, to automatically find interest tags for non-famous users in social network such as Twitter. Instead of extracting tags from text posts, tags of non-famous users are inferred from interest topics of famous users. With the proposed model, the formulation of social relationship between non-famous users and famous user is simulated and interest tags of famous users are exploited to supervise the training of the model and to make use of latent relation among famous users. Furthermore, the influence of popularity of famous user and popular tags are considered, and tags of non-famous users are ranked based on random walk model. Experiments were conducted on Twitter real datasets. Comparison with state-of-the-art methods shows that our method is more superior in terms of both ranking and quality of the tagging results. [ABSTRACT FROM AUTHOR]

In the big data set around the world, cultural communication in a single-layer social network cannot handle data in a two-tier social network. Combined with the characteristics of cultural communication, a two-layer coupled social network model for predicting cultural information dissemination is proposed. According to the law of big data set in the process of cultural communication, the ethical review and theoretical construction of cultural network communication was carried out. Combining the online two-layer coupling network and the CRF word segmentation algorithm, the known link relationship is obtained, and the feature attributes of the network are extracted. This paper mainly completed the construction of online social network link prediction. Starting from the topological structure of two-layer coupled social network, based on the association rules to analyze the data generated by information dissemination between two-layer coupled network nodes, a two-layer coupled network information propagation law model is proposed. The prediction and construction of the cultural information communication link in the online social network is completed, the process of data opening and sharing is accelerated, and the privacy and copyright issues in the process of cultural communication are solved. The influence of immune node and node self-healing time on the cultural information dissemination process of two-layer coupled social network is discussed. By comparing the information dissemination in social networks and the information dissemination in two-layer coupled social networks, the control of certain lyric cultures can be effectively prevented. The experimental results show that it has reference value. [ABSTRACT FROM AUTHOR]