Deliberative democracy started out as an ideal for mass democracy. Lately, however, its large-scale ambitions have mostly been shelved. This article revivifies the ideal of mass deliberative democracy by offering a clear mechanism by which everyone in the community can be included in the same conversation. The trick is to make use of people’s overlapping social communicative networks through which informal deliberative exchanges already occur on an everyday basis. Far from being derailed by threats of polarization, echo chambers, and (...) motivated reasoning, informal networked deliberation can indeed put everyone in touch, directly or indirectly, with everyone else. (shrink)

Drawing on interviews with decision makers in multinational corporations (MNCs) in South Korea, we examine the role of informal networks in the social exclusion of women in the workforce. Although legislation in the country is in favor of gender equality, we found that informal barriers in the workplace remain difficult to overcome. Informal networks in Korea, yongo, present an ethical issue in the workplace, as they tend to socially exclude women, limiting possibilities for their participation and career progression. (...) We found that informal networks are pervasive and strong because of the informal institutions in which they are embedded and that there is a complex interplay between informal networks and informal institutions that socially excludes women. Due to difficulties accessing yongo, women appear to build inmaek, a network type that is more open and accessible. We also found that MNCs in Korea can compensate for the lack of local informal networks for their female employees. However, despite providing a more supportive environment for women at work, gender equality policies in MNCs are not yet as effective as they could be due to the dynamics of the workplace and the fact that the policies are not tailored to the local context. We have seen evidence in recent years that MNCs can serve as role models for implementing gender equality policies by creating a more inclusive work environment and demonstrating leadership commitment and support. (shrink)

The question of whether “genetic information” is a merely causal factor in development or can be made sense of semantically, in a way analogous to a language or other type of representation, has generated a long debate in the philosophy of biology. It is intimately connected with another intense debate, concerning the limits of genetic determinism. In this paper I argue that widespread attempts to draw analogies between genetic information and information contained in books, blueprints or computer (...) programs, are fundamentally inadequate. In development, gene exons are the central part of an intricate and densely ramified semantic Genetic Informational Network. DNA in the entire genome is in a state of continuous positive and negative feedback with itself and with its ‘environment’, and is ‘read’ and acted upon by the cell in various alternative and complementary ways. The linear combinatorial coding relation between codons and amino acids is but one aspect of semantic genetic information, which is, when considered in its entirety, a far wider and richer concept. (shrink)

Link trustworthiness evaluation is a crucial task for information networks to evaluate the probability of a link being true in a heterogeneous information network. This task can significantly influence the effectiveness of downstream analysis. However, the performance of existing evaluation methods is limited, as they can only utilize incomplete or one-sided information from a single HIN. To address this problem, we propose a novel multi-HIN link trustworthiness evaluation model that leverages information across multiple related HINs (...) to accomplish link trustworthiness evaluation tasks inherently and efficiently. We present an effective method to evaluate and select informative pairs across HINs and an integrated training procedure to balance inner-HIN and inter-HIN trustworthiness. Experiments on a real-world dataset demonstrate that our proposed model outperforms baseline methods and achieves the best accuracy and F1-score in downstream tasks of HINs. (shrink)

It is widely accepted that the way information transfers across networks depends importantly on the structure of the network. Here, we show that the mechanism of information transfer is crucial: in many respects the effect of the specific transfer mechanism swamps network effects. Results are demonstrated in terms of three different types of transfer mechanism: germs, genes, and memes. With an emphasis on the specific case of transfer between sub-networks, we explore both the dynamics of each (...) of these across networks and a measure of their comparative fitness. Germ and meme transfer exhibit very different dynamics across linked networks. For germs, measured in terms of time to total infection, network type rather than degree of linkage between sub-networks is the primary factor. For memes or belief transfer, measured in terms of time to consensus, it is the opposite: degree of linkage trumps network type in importance. The dynamics of genetic information transfer is unlike either germs or memes. Transfer of genetic information is robust across network differences to which both germs and memes prove sensitive. We also consider function: how well germ, gene, and meme transfer mechanisms can meet their respective objectives of infecting the population, mixing and transferring genetic information, and spreading a message. A shared formal measure of fitness is introduced for purposes of comparison, again with an emphasis on linked sub-networks. Meme transfer proves superior to transfer by genetic reproduction on that measure, with both memes and genes superior to infection dynamics across all networks types. What kinds of network structure optimize fitness also differ among the three. Both germs and genes show fairly stable fitness with added links between sub-networks, but genes show greater sensitivity to the structure of sub-networks at issue. Belief transfer, in contrast to the other two, shows a clear decline in fitness with increasingly connected networks. When it comes to understanding how information moves on networks, our results indicate that questions of information dynamics on networks cannot be answered in terms of networks alone. A primary role is played by the specific mechanism of information transfer at issue. We must first ask about how a particular type of information moves. (shrink)

In this article, I analyze survey data from more than 1,000 financial services employees to understand how gender inequality manifests itself in employees' informal networks. I found that even when Black and white women had jobs in which they controlled organizational resources and had ties to powerful employees, they received less work-related help from their network members than did white men. Drawing on status characteristics theory, I explain that network members were less likely to invest in women than in (...) white men because of cultural beliefs that rank women below that of white men. While past research has documented how employers use gender to rank workers and distribute rewards unequally, my research indicates that workers use gender to categorize and rank their network members as well. (shrink)

Farmers’ willingness and ability to adapt to climate change are in part influenced by their social networks and sources of information. Drawing on assemblage theory and social network analysis in a novel way, this study explores the influence of Oregonian small farmers’ social and informational networks on their beliefs about and responses to climate change. The use of assemblage theory, which focuses on many disparate elements as they co-function in a space, allows for multiple entities within farmers’ (...) networks and the ways they interact to be examined, while the use of social network analysis highlights broader patterns in the structure and composition of farmers’ networks. Theoretically, this study brings these two distinct yet similar bodies of theory and methodologies together for the first time to expand the utility of both fields and explore farmers’ networks in a novel way. Results indicate that small farmers’ connections to other farmers and media in their networks are influencing their beliefs about climate change, while their responses are influenced by their ties to various agricultural and climatological information sources, as well as other nearby farmers. Finally, while farmers’ ties to other farmers are largely limited to those nearby, certain central individuals and entities, particularly beginning farmers, can act as bridges linking distinct groups of farmers. An understanding of these networks can be used to better disseminate critical information, such as forecasts and adaptation strategies, to help farmers adapt. (shrink)

Understanding the dynamics of information is crucial to many areas of research, both inside and outside of philosophy. Using computer simulations of three kinds of information, germs, genes, and memes, we show that the mechanism of information transfer often swamps network structure in terms of its effects on both the dynamics and the fitness of the information. This insight has both obvious and subtle implications for a number of questions in philosophy, including questions about the nature (...) of information, whether there is genetic information, and how to arrange scientific communities. (shrink)

The United States, like other countries facing rising health care costs, is pursuing a commitment to interoperable electronic health records. Electronic records, it is thought, have the potential to reduce the risks of error, improve care coordination, monitor care quality, enable patients to participate more fully in care management, and provide the data needed for research and surveillance. Interoperable electronic health records on a national scale — the ideal of a national health information network — seem likely to magnify (...) these advantages. Thus, the recent economic stimulus package contains considerable funding for the development of “health information technology architecture that will support the nationwide electronic exchange and use of health information in a secure, private, and accurate manner.”. (shrink)

In this article, we propose to comprehend the corruption mechanisms of tender bidding processes in terms of Human Resource Management (HRM) practices within informal networks. Taking the context of Kazakhstan, we analyze the behavior of individual actors as members of informal networks. Our analysis shows that both corruption and anti-corruption mechanisms can be explained in terms of HRM practices such as (camouflaged) recruitment (e.g., of powerful government officials via network ties), compensation (e.g., kickbacks for corruption; social recognition or (...) shame for anti-corruption) and performance management (e.g., demonstrative punishment for corruption; extreme formalization, peer pressure or social sanctions for anti-corruption). (shrink)

In this article, we propose to comprehend the corruption mechanisms of tender bidding processes in terms of Human Resource Management practices within informal networks. Taking the context of Kazakhstan, we analyze the behavior of individual actors as members of informal networks. Our analysis shows that both corruption and anti-corruption mechanisms can be explained in terms of HRM practices such as recruitment, compensation and performance management.

Heterogeneous information networks can naturally simulate complex objects, and they can enrich recommendation systems according to the connections between different types of objects. At present, a large number of recommendation algorithms based on heterogeneous information networks have been proposed. However, the existing algorithms cannot extract and combine the structural features in heterogeneous information networks. Therefore, this paper proposes an efficient recommendation algorithm based on heterogeneous information network, which uses the characteristics of graph convolution (...) neural network to automatically learn node information to extract heterogeneous information and avoid errors caused by the manual search for metapaths. Furthermore, by fully considering the scoring relationship between nodes, a calculation strategy combining heterogeneous information and a scoring information fusion strategy is proposed to solve the scoring between nodes, which makes the prediction scoring more accurate. Finally, by updating the nodes, the training scale is reduced, and the calculation efficiency is improved. The study conducted a large number of experiments on three real data sets with millions of edges. The results of the experiments show that compared with PMF, SemRec, and other algorithms, the proposed algorithm improves the recommendation accuracy MAE by approximately 3% and the RMSE by approximately 8% and reduces the time consumption significantly. (shrink)

Since the collapse of the Soviet Union, Moscow has become a global city with a vibrant urban and cultural life-one of the most expensive capitals in the world with famous clubs and restaurants, as well as one of the most popular destinations for city workers and diplomats. Has corruption been instrumental in Moscow's development? The answer is complicated and in many ways a matter of definitions. It depends on whether one considers informal practices-inherited from Soviet times as well as new (...) ones-as corrupt and how one conceptualizes corruption. I will illustrate some of these complications for the case of the Soviet practice of blat, explain its "monetization" and its evolving relationship with corruption in the post-Soviet transition, and analyze the role of informal networks in present-day Russia. (shrink)

How did one man living on an island come to acquire information about the rest of the vast archipelago? This article traces the inter-island information networks of Georg Everhard Rumphius (1627–1702), an employee of the Dutch East India Company, who was able to explore the natural world of the wider archipelago without ever leaving the Moluccan island of Ambon. This article demonstrates the complexities of Rumphius's inter-island networks, as he collected information about plants and objects (...) from islands near and far. Using his administrative, commercial and household networks, Rumphius was able to interact with local actors from across the social spectrum, whose own active collection, mediation and circulation of objects and information overlapped with imperial activities in the archipelago. This article examines Rumphius as both a collector and a mediator, who negotiated between multiple economies of exchange and translated information from different islands for his distant European readership. Such practices of localized translation demonstrate how knowledge produced on one island was the product of criss-crossing inter-island networks, as the information concerned underwent its own complicated processes of transmission and transformation within the archipelago before reaching its intended audience in Europe. (shrink)

Investor recommendation is a critical and challenging task for startups, which can assist startups in locating suitable investors and enhancing the possibility of obtaining investment. While some efforts have been made for investor recommendation, few of them explore the impact of startups’ features, including partners, rounds, and fields, to investor recommendation performance. Along this line, in this paper, with the help of the heterogeneous information network, we propose a FEatures’ COntribution Measurement approach of startups on investor recommendation, named FECOM. (...) Specifically, we construct the venture capital heterogeneous information network at first. Then, we define six venture capital metapaths to represent the features of startups that we focus on. In this way, we can measure the contribution of startups’ features on the investor recommendation task by validating the recommendation performance based on different metapaths. Finally, we extract four practical rules to assist in further investment tasks by using our proposed FECOM approach. (shrink)

The growing use of interoperable electronic health records is likely to have significant effects on the physician-patient relationship. This relationship involves two-way trust: of the physician in patients, and of the patients in their providers. Interoperable records opens up this relationship to further view, with consequences that may both enhance and undermine trust. On the one hand, physicians may learn that information from their patients is — or is not — to be trusted. On the other hand, patients may (...) learn from the increased oversight made possible by electronic records that their trust in their physicians is — or is not — warranted. Release of information through new methods of surveillance may also undermine patient trust. The article concludes that because trust is fragile, attention to transparency and confidentiality in the use of interoperable electronic records is essential. (shrink)

Healthcare Providers advising patient surrogates on the appropriateness of continued care for comatose patients have often been sharply criticized for coercive behavior toward patient surrogates; with failing to provide them with adequate information; and for a general failure to adequately cinsider the cimplex needs and hopes of patients, their surrogates, and caregivers. Because decisions on the continuation or withdrawal of care often need the legal approval of surrogates the failure of both medical personnel and patient families to understand each (...) other's priorities may lead to ethical and interpersonal conflict. (shrink)

The article explores integration of knowledge-enabling digital technology into community functions through the development of local Digital Communities of Practice. This analysis includes both general considerations—in terms of domain, community, and practice dimensions—as well as results from an exploratory research project in Minnesota. The domain is described as integrated deployment of virtual services (education, human services, government) in local communities; the community is comprised of the local stakeholders and residents that would use or benefit from such services; and the practice (...) is considered as a decision-making processes for designing and deploying these services. The paper concludes with research and policy considerations for providing an enduring source of knowledge about local virtual services, needs, and solutions. (shrink)

The article addresses the problem of how semantic information can be upgraded to knowledge. The introductory section explains the technical terminology and the relevant background. Section 2 argues that, for semantic information to be upgraded to knowledge, it is necessary and sufficient to be embedded in a network of questions and answers that correctly accounts for it. Section 3 shows that an information flow network of type A fulfils such a requirement, by warranting that the erotetic deficit, (...) characterising the target semantic information t by default, is correctly satisfied by the information flow of correct answers provided by an informational source s. Section 4 illustrates some of the major advantages of such a Network Theory of Account (NTA) and clears the ground of a few potential difficulties. Section 5 clarifies why NTA and an informational analysis of knowledge, according to which knowledge is accounted semantic information, is not subject to Gettier-type counterexamples. A concluding section briefly summarises the results obtained. (shrink)

Virus and information spreading dynamics widely exist in complex systems. However, systematic study still lacks for the interacting spreading dynamics between the two types of dynamics. This paper proposes a mathematical model on multiplex networks, which considers the heterogeneous susceptibility and infectivity in two subnetworks. By using a heterogeneous mean-field theory, we studied the dynamic process and outbreak threshold of the system. Through extensive numerical simulations on artificial networks, we find that the virus’s spreading dynamics can be (...) suppressed by increasing the information spreading probability, decreasing the protection power, or decreasing the susceptibility and infectivity. (shrink)

This paper concerns an information extraction process for building a dynamic legislation network from legal documents. Unlike supervised learning approaches which require additional calculations, the idea here is to apply information extraction methodologies by identifying distinct expressions in legal text in order to extract network information. The study highlights the importance of data accuracy in network analysis and improves approximate string matching techniques to produce reliable network data-sets with more than 98% precision and recall. The applications and (...) the complexity of the created dynamic legislation network are also discussed and challenged. (shrink)

Beyond belief change and meme adoption, both genetics and infection have been spoken of in terms of information transfer. What we examine here, concentrating on the specific case of transfer between sub-networks, are the differences in network dynamics in these cases: the different network dynamics of germs, genes, and memes. Germs and memes, it turns out, exhibit a very different dynamics across networks. For infection, measured in terms of time to total infection, it is network type rather (...) than degree of linkage between sub-networks that is of primary importance. For belief transfer, measured in terms of time to consensus, it is degree of linkage rather than network type that is crucial. Genes model each of these other dynamics in part, but match neither in full. For genetics, like belief transfer and unlike infection, network type makes little difference. Like infection and unlike belief, on the other hand, the dynamics of genetic information transfer within single and between linked networks are much the same. In ways both surprising and intriguing, transfer of genetic information seems to be robust across network differences crucial for the other two. (shrink)

This article brings together two research fields in applied ethics - namely, information ethics and business ethics- which deal with the ethical impact of information and communication technologies but that, so far, have remained largely independent. Its goal is to articulate and defend an informational approach to the conceptual foundation of business ethics, by using ideas and methods developed in information ethics, in view of the convergence of the two fields in an increasingly networked society.

Online social networks captured the attention of the masses by offering attractive means of sharing personal information and developing social relationships. People expose personal information about their lives on OSNs. This may result in undesirable consequences of users’ personal information leakage to an unwanted audience and raises privacy concerns. The issue of privacy has received a significant attention in both the research literature and the mainstream media. In this paper, we present results of an empirical study (...) that measure users’ attitude towards interpersonal privacy concerns in OSNs. The results demonstrated a serious mismatch between privacy concerns of users and their information sharing behavior. In addition, it indicated that strangers are part of user social circles, this makes privacy protection more complicated, and introduce an insider threat, whereas all existing privacy tools allow users to manage the outsider threat. Information and friend segregation strategies are suggested on the basis of user information disclosure and interaction pattern. We conclude that sensitivity of information and frequency of interaction, both, play a vital role in information and friend segregation. (shrink)

Big Data research is currently split on whether and to what extent Twitter can be characterized as an informational or social network. We contribute to this line of inquiry through an investigation of digital humanities scholars’ uses and gratifications of Twitter. We conducted a thematic analysis of 25 semi-structured interview transcripts to learn about these scholars’ professional use of Twitter. Our findings show that Twitter is considered a critical tool for informal communication within DH invisible colleges, functioning at varying levels (...) as both an information network and a social network. We find that Twitter follow relationships reflect common academic interests and are closely tied to scholars’ pre-existing social ties and conference or event co-attendance. The concept of the invisible college continues to be relevant but requires revisiting. The invisible college formed on Twitter is messy, consisting of overlapping social contexts, scholars with different habits of engagement, and both formal and informal ties. Our research illustrates the value of using multiple methods to explore the complex questions arising from Big Data studies and points toward future research that could implement Big Data techniques on a small scale, focusing on sub-topics or emerging fields, to expose the nature of scholars’ invisible colleges made visible on Twitter. (shrink)

PurposeThis paper aims to investigate behavioural changes related to self-censorship (SC) in social networking sites (SNSs) as new methods of online surveillance are introduced. In particular, it examines the relationships between SC and four related factors: privacy concerns (PC), privacy awareness (PA), perceived vulnerability (PV) and information management (IM).Design/methodology/approachA national wide survey was conducted in the UK (N= 519). The data were analysed to present both descriptive and inferential statistical findings.FindingsThe level of online SC increases as the level of (...) privacy concern increases. The level of privacy concern increases as the levels of PA and PV increase and the level of effective IM decreases.Originality/valueThis study extends the literature on online SC, showing that PCs increase the level of SC in SNSs. It provides support for three antecedent factors to PC which impact upon levels of SC when communicating in SNSs. (shrink)

This article explores the norms that govern regular users’ acts of sharing content on social networking sites. Many debates on how to counteract misinformation on Social Networking Sites focus on the epistemic norms of testimony, implicitly assuming that the users’ acts of sharing should fall under the same norms as those for posting original content. I challenge this assumption by proposing a non-epistemic interpretation of (mis) information sharing on social networking sites which I construe as infrastructures for forms of (...) life found online. Misinformation sharing belongs more in the realm of rumour spreading and gossiping rather than in the information-giving language games. However, the norms for sharing cannot be fixed in advance, as these emerge at the interaction between the platforms’ explicit rules, local norms established by user practices, and a meta-norm of sociality. This unpredictability does not leave us with a normative void as an important user responsibility still remains, namely that of making the context of the sharing gesture explicit. If users will clarify how their gestures of sharing are meant to be interpreted by others, they will implicitly assume responsibility for possible misunderstandings based on omissions, and the harms of shared misinformation can be diminished. (shrink)

Network analysis views complex systems as networks with well-defined structural properties that account for their complexity. These characteristics, which include scale-free behavior, small worlds and communities, are not to be found in networks such as random graphs and lattices that do not correspond to complex systems. They provide therefore a robust ground for claiming the existence of “complex networks” as a non-trivial subset of networks. The theory of complex networks has thus been successful in making (...) systematically explicit relevant marks of complexity in the form of structural properties, and this success is at the root of its current popularity. Much less systematic has been, on the other hand, the definition of the properties of the building components of complex networks. The obvious assumption is that these components must be nodes and links. Generally, however, the internal structure of nodes is not taken into account, and links are serendipitously identified by the perspective with which one looks at the network to be analyzed. For instance, if the nodes are Web pages that contain information about scientific papers, one point of view will match the relevant links with hyperlinks to similar Web pages, and another with citations of other articles. We intend to contribute here a systematic approach to the identification of the components of a complex network that is based on information theory. The approach hinges on some recent results arising from the convergence between the theory of complex networks and probabilistic techniques for content mining. At its core there is the idea that nodes in a complex network correspond to basic information units from which links are extracted via methods of machine learning. Hence the links themselves are viewed as emergent properties, similarly to the broader structural properties mentioned above. Indeed, beside rounding up the theory, this approach based on learning has clear practical benefits, in that it makes networks emerge from arbitrary information domains. We provide examples and applications in a variety of contexts, starting from an information-theoretic reconstruction of the well-known distinction between “strong links” and “weak links” and then delving into specific applications such as business process management and analysis of policy making. (shrink)

In the realistic world, various individuals have distinct personalities, preferences, and attitudes toward new information and behavior acceptance, called population heterogeneity. It is seldom taken into account and theoretically analyzed in information propagation on a weighted network. Therefore, we divide individuals into fashionable and conservative individuals according to their passion degree and willingness for novel behaviors acceptance. Then, we build two behavior adoption threshold models corresponding to fashionable and conservative individuals on the weighted network to explore the effect (...) of population heterogeneity on information propagation. Next, a partition theory based on edge weight and population heterogeneity is proposed to qualitatively analyze the information propagation mechanism. The theoretical analyses and simulation results show that fashionable individuals promote information propagation and behavior adoption. More importantly, the crossover phenomena of phase transition appear. When the fraction of fashionable individuals is relatively large, the increasing pattern of the final adoption size shows a second-order continuous phase transition. In comparison, the increasing pattern alters to first-order discontinuous phase transition with the decrease of the fraction of fashionable individuals. Moreover, reducing weight distribution heterogeneity promotes information propagation and slightly accelerates the change of the phase transition pattern from the first-order discontinuous to the second-order continuous. Besides, increasing the degree distribution heterogeneity accelerates the change of the phase transition pattern. Finally, our theoretical analyses coincide well with the simulation results. (shrink)

This paper provides an analysis of the complex global reproduction networks driving the rapidly expanding cross-border surrogacy industry in Asia’s reproductive bioeconomy. It sheds light on the unique features of informal surrogacy networks, notable for their flexible business ties and non-standardized surrogate mother recruitment. These factors contribute to heightened vulnerability for surrogate mothers operating within these networks. While previous literature has underscored the merits of labor law in regulating the surrogacy industry, its application in informal cross-border surrogacy (...) remains under-examined. To address this gap, this research delves into innovative labor law strategies with potential to better regulate the surrogacy sector. Drawing inspiration from progressive labor regulations and supply chain strategies in Bulgaria and Australia, the proposed model aims to redefine the traditional employment relationship. This shift is aimed at bolstering protection for surrogate mothers and enforcing accountability throughout the surrogacy business network. The model further advocates for a collective framework that fosters collaboration and mandates the documentation and registration of surrogacy contracts. Moreover, it underscores the critical significance of international collaboration in bridging regulatory gaps and distributing accountability across consumer and supply states. (shrink)

Shows how digital capitalism has shaped human rights practices What happens to the cultural politics of human rights when atrocities are rendered calculable, abuses are transformed into data, and victims become vectors? As human rights organisations have increasingly embraced information technologies this 'datafication' of rights has become both a reality and a pressing concern, one inextricably tangled up with questions regarding the broader political valences of human rights. Combining contemporary social and cultural theory with archival research and original ethnographic (...) work, Josh Bowsher resituates recent critiques of human rights within ongoing theoretical discussions concerning informational capitalism, digital culture and the politics of data. Critically analysing the contemporary human rights movement as an informational politics, Bowsher provides a new conceptual agenda for both exploring and overcoming the limits of human rights in an era shaped by the data flows, network infrastructures and informational logic of late capitalism. Josh Bowsher is Lecturer in Sociology at Brunel University. (shrink)

This book deals with the major ethical and social implications of computer networking and its technological development. In this book, a number of leading thinkers--philosophers, computer scientists and researchers--address some fundamental questions posed by the new technology.

This paper describes how Tononi’s information integration theory of consciousness was used to make detailed predictions about the distribution of phenomenal states in a spiking neural network. This network had approximately 18,000 neurons and 700,000 connections and it used models of emotion and imagination to control the eye movements of a virtual robot and avoid ‘negative’ stimuli. The first stage in the analysis was the development of a formal definition of Tononi’s theory of consciousness. The network was then analysed (...) for information integration and detailed predictions were made about the distribution of consciousness for each time step of recorded activity. This work demonstrates how an artificial system can be analysed for consciousness using a particular theory and in the future this approach could be used to make predictions about the phenomenal states associated with biological systems. (shrink)

The wanton dissemination of network pseudohealth information has brought great harm to people’s health, life, and property. It is important to detect and identify network pseudohealth information. Based on this, this paper defines the concepts of pseudohealth information, data block, and data block integration, designs an architecture that combines the latent Dirichlet allocation algorithm and data block update integration, and proposes the combination algorithm model. In addition, crawler technology is used to crawl the pseudohealth information transmitted (...) on the Sina Weibo platform during the “epidemic situation” from February to March 2020 for the simulation test on the experimental case dataset. The research results show that the LDA model can deeply mine the semantic information of network pseudohealth information, obtain the features of document-topic distribution, and classify and train topic features as input variables; the dataset partitioning method can effectively block data according to the text attributes and class labels of network pseudohealth information and can accurately classify and integrate the block data through the data block reintegration method; and considering that the combination model has certain limitations on the detection of network pseudohealth information, the support vector machine model can extract the granularity content of data blocks in pseudohealth information in real time, thus greatly improving the recognition performance of the combination model. (shrink)

Social networking sites have challenged ethical issues about users’ information security and privacy. SNS users are concerned about their privacy and need to control the information they share and its use. This paper examines the security of SNS by taking a look at the influence of users’ perceived control of information over their information-sharing behaviors. Employing an empirical study, this paper demonstrates the importance of perceived control in SNS users’ information-sharing behaviors. Specifically, perceived control has (...) been found to be negatively related to perceived privacy risk and attitude toward information sharing, which in turn has an impact on their information-sharing behaviors. In addition, gender has been shown to be an important factor that moderates the influences of both perceived control and perceived privacy risk on SNS users’ attitudes toward information sharing. Theoretical and practical implications are discussed. (shrink)

This essay advances two sets of critical observations about Manuel Castells's suggestion and detailed elaboration of the idea that modern society from the 1980s onwards constitutes a network society and that the unity in the diversity of global restructuring has to be seen in the massive deployment of information and communication technologies in all spheres of modern social life. The criticism attends to the possibility that the emphasis on the social role of information technologies in advanced society amounts (...) to a modern version of `technological determinism'. A discussion of the so-called productivity paradox shows that cultural and social processes rather than technological regimes continue to be more important for the evolution of society. (shrink)

We study the synchronization of complex networks by using event-sampling information. The nodes of the network are connected with event-triggered communication via multiple couplings. The couplings are split into several channels. Not all the channels are connected. Only a part of the states of each node can be communicated by the channels. An event detector is designed for each channel to independently determine the sampling moments. The couplings of the network are partial and event-triggered. Both features make that (...) less information can be used for synchronization. The pinning controllers are also designed based on the sampled information. By establishing a time-dependent Lyapunov functional and utilizing an efficient event condition, we derive less conservative criteria for the synchronization of complex networks. Finally, the effectiveness of our main results is verified by an illustrative example, and comparisons are also presented to show how much conservatism can be reduced. (shrink)

This paper is concerned with the modeling of neural systems regarded as information processing entities. I investigate the various dynamic regimes that are accessible in neural networks considered as nonlinear adaptive dynamic systems. The possibilities of obtaining steady, oscillatory or chaotic regimes are illustrated with different neural network models. Some aspects of the dependence of the dynamic regimes upon the synaptic couplings are examined. I emphasize the role that the various regimes may play to support information processing (...) abilities. I present an example where controlled transient evolutions in a neural network, are used to model the regulation of motor activities by the cerebellar cortex. (shrink)