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COVID-19 causes a jarring impact on the livelihoods of people in Malaysia and globally. To prevent an outbreak in the community, identifying the likely sources of infection (hotspots) of COVID-19 is important. The goal of this study is to formulate a bipartite network model of COVID-19 transmissions by incorporating patient mobility data to address the assumption on population homogeneity made in the conventional models and focus on indirect transmission. Two types of nodes – human and location – are the main concern in the research scenario. 21 location nodes and 31 human nodes are identified from a patient’s pre-processed mobility data. The parameters used in this study for location node and human node quantifications are the ventilation rate of a location and the environmental properties of the location that affect the stability of the virus such as temperature and relative humidity. The summation rule is applied to quantify all nodes in the network and the link weight between the human node and the location node. The ranking of location and human nodes in this network is computed using a web search algorithm. This model is considered verified as the error obtained from the comparison made between the benchmark model and the COVID-19 bipartite network model is small. As a result, the higher ranking of the location is denoted as a hotspot in this study, and for a human node attached to this node will be ranked higher in the human node ranking. Consequently, the hotspot has a higher risk of transmission compared to other locations. These findings are proposed to provide a framework for public health authorities to identify the sources of infection and high-risk groups of people in the COVID-19 cases to control the transmission at the initial stage.

The article deals with the history of the formation, current state and prospects for the development of social informatics as a current direction in science and education in Russia. The article offers mainly a personal view of the author, who has been involved in shaping social informatics in Russia for the last three decades. The article presents the distinctive features of the Russian scientific school of social informatics and its priorities in the formation of this field. The main directions of research in the field of social informatics in Russia in the context of the formation of the global information society are determined. Emphasis is placed on the interdisciplinary nature of many issues related to social informatics and their systematic study. Finally, the article summarizes the current necessity for the deep study of issues related to social informatics, e.g., information inequality, information crime, cyberbullies, manipulation of consciousness, virtualization of society, information wars, information poverty, information culture, and using computers to analyse social phenomena such as communication via social media. It is important not only in the area of scientific research but also in the system of secondary and higher education and training of scholars.

Increasing demand for personalized tours for tourists travel in an urban area motivates more attention to points of interest (POI) and tour recommendation services. Recently, the granularity of POI has been discussed to provide more detailed information for tour planning, which supports both inside and outside routes that would improve tourists' travel experience. Such tour recommendation systems require a predefined POI database with different granularities, but existing POI discovery methods do not consider the granularity of POI well and treat all POIs as the same scale. On the other hand, the parameters also need to be tuned for different cities, which is not a trivial process. To this end, we propose a city adaptive clustering framework for discovering POIs with different granularities in this article. Our proposed method takes advantage of two clustering algorithms and is adaptive to different cities due to automatic identification of suitable parameters for different datasets. Experiments on two real-world social image datasets reveal the effectiveness of our proposed framework. Finally, the discovered POIs with two levels of granularity are successfully applied on inner and outside tour planning.

This paper introduces the praxeologically grounded research programme on socio-informatics developed at the University of Siegen and the International Institute for Socio-Informatics in Germany. We outline our methodological framework of grounded design, guiding and binding together a variety of different engagements in practice which we call design case studies (DCS). While grounded design is applied to a broad variety of different areas, in this paper we deal specifically with our engagements in support of communities and political activists. To exemplify our approach, we present one DCS: It focuses on the participatory development of a computer club in the High Atlas as a facilitation infrastructure to support public community participation in the process of modernization and social transformation in the Maghreb. Insights into the project context, the objectives and methodology and the depiction of some of its first findings lays the ground for the discussion of socio-informatics research principles.

Today, data security is an increasingly hot topic, and thus also the security and reliability of end-user identity verification, i.e. authentication. In recent years, banks began to substitute password authentication by more secure ways of authentication because passwords were not considered to be secure enough. Current legislation even forces banks to implement multi-factor authentication of their clients. Banks, therefore, consider using biometric authentication as one of the possible ways. To verify a user's identity, biometric authentication uses unique biometric characteristics of the user. Examples of such methods are facial recognition, iris scanning, fingerprints, and so on. This paper deals with another biometric feature that could be used for authentication in mobile banking applications; as almost all mobile phones have an integrated camera, hand authentication can make a banking information system more secure and its user interface more convenient. Although the idea of hand biometric authentication is not entirely new and there exist many ways of implementing it, our approach based on using convolutional neural networks is not only innovative, but its results are promising as well. This paper presents a modern approach to identifying users by convolutional neural networks when this type of neural network is used both for hand features extraction and bank user identity validation.

Even if we think that all the computer systems that are in operation work perfectly, the background might not be as it seems. We might face some faulty web interactions on a popular website or software as well. User behaviors are vital for developers in creating a satisfying computer system. in the aim of this study was threefold. Firstly, to determine if users’ tolerance of different kinds of faulty web interactions changes depending on the environment, and then to find how users’ behaviors differ when they encounter a faulty web interaction. Lastly, to detect how faulty web interactions shape users’ perceptions. To achieve these aims, we conducted a test on a manipulated mobile e-commerce website with 11 tasks including five faulty ones. Participants were not informed that the test includes faulty tasks. Faulty tasks consist of different kinds of web errors: Not Responding, Blank Page, Connection Timeout (HTTP-500), Not Found (HTTP-404), and Redirect (HTTP-301). The other tasks were organized as dummy tasks, and they were not examined. In the results of this study, we reached quantitative (for the collection of quantitative data, we used a Tolerance Evaluation Scale (TES) that we developed for this study) and qualitative findings. According to the quantitative findings, there is no difference between the tolerance levels of users for different environments. On the other hand, it was determined that when there is an error that includes feedback, user tolerance is affected positively. In addition to this, it can be seen that users have a low tolerance towards giving another chance to any kind of website which has a faulty interaction. In terms of qualitative findings, participants emphasized that it does not matter what purpose a website serves, the errors give an amateur impression by damaging usability and professionalism.

Czech government institutions commissioned a research on extracting usual unit prices from public IT contracts to aid future public tender sizing. The goal of the project is to obtain millions of contracts from the public register, convert them to full text, extract unit prices from the text and publish a pricelist of IT industry manday prices. This paper designs the process and method of price extraction, demonstrates and evaluates the result on five iterations of extraction and discusses the experience of two years of project performance. The process is designed as a set of repeatable workflows and specified activity and role description. The method is designed as a combination of automated and manual actions. Due to the format and content variability of involved documents and the low mistake tolerance, the possibility of automated extraction of unit prices from full text contract is limited, and human workforce for validation is crucial.

Digitalization in human resource management helps enterprises to modernize HR functions and provides them with a competitive advantage. At the same time, it requires a change in working style and entails a change in the demand for HR competencies. The purpose of this paper is to introduce the phenomenon of digitalization in the literature, explore its current key benefits and risks, and analyse its influence on HR professionals´ competencies and roles. The qualitative research includes an analysis of the secondary data describing the existing level of digital skills based on the reactions of more than 7,000 respondents from six EU member states (Germany, Finland, United Kingdom, Portugal, Sweden, and Slovakia). The primary data analysis concerning HR social media competencies collected in five European countries which participated in the SHARPEN project is also presented here. The current trends in HR professional competencies are also described in this paper. The results obtained show that HR professionals tend to be slightly reluctant to adopt technology. The results also confirmed the importance of digitalization for human resources and the increasing demand for digital skills in recent years.

Cryptocurrencies have become a major phenomenon in recent years. For IT, a breakthrough is both the cryptocurrency itself as a commodity and the technology that cryptocurrency development has brought. The article focuses on the bitcoin cryptocurrency as the most important cryptocurrency. A relatively unexplored topic is what goods or services are purchased for bitcoins. To track what bitcoins are spent on, it is necessary to look for places that are dedicated to trading cryptocurrencies. The bitcointalk.org forum was chosen as a source for our data mining. The aim of the article is to find an answer to the research question: What are bitcoins on the discussion forum bitcointalk.org planned to be spent on? As part of the research, an application was developed using a PHP script to gather information from the discussion forum (bitcointalk.org). There is some evidence which suggests what types of products or services people spend cryptocurrencies on. This research has proven that cryptocurrencies are used to buy and sell goods or services in the electronics and computer world segments. Today, these segments are widespread, which may speed up the integration of cryptocurrencies into everyday life. This applies, of course, only if the risks associated with cryptocurrencies do not increase.

The aim of the article is to detect and review existing topic modelling methods of Latent Dirichlet Allocation and their modifications usable in Voice of Customer analysis. Voice of Customer is expressed mainly through textual comments which often focus on the evaluation of products or services the customer consumes. The most studied data source are customer reviews which contain next to the textual comments also ratings in form of scales. The aim of the topic models is to mine the topics and their aspects the customers are evaluating in their reviews and assign to them a particular sentiment or emotion. The author completed a systematic literature review of peer-reviewed published journal articles indexed in leading databases of Scopus and Web of Science and concerning the current use of Latent Dirichlet Allocation model variants in Voice of Customer textual analysis for performing the tasks of aspect detection, emotion detection, personality detection and sentiment assignation. In total, 38 modifications of the LDA model were identified with the reference to their first application in the research of text analytics. The review is intended for researchers in customer analytics the field of sentiment or emotion detection, and moreover as results from the review, for studies in personality recognition based on the textual data. The review offers a basic overview and comparison of LDA modifications which can be considered as a knowledge baseline for selection in a specific application. The scope of the literature examination is limited to the period of years 2003–2018 with the application relevant to the analysis of Voice of Customer subjective textual data only which is closely connected to the area of marketing or customer relationship management.

Data mining methods are still more popular, even in domains where there is traditionally limited support by analytical tools and where the analyst´s manual work still prevails. Using these methods in the fiscal domain enables deeper analysis and can bring new findings. The deployment of data mining methods is one part of the OpenBudgets.eu project, which focuses on transparency and accountability in the public funds management. This overview article summarizes selected experiences of the authors of the project from the development, implementation and application of selected data mining methods on mining fiscal data. These methods are integrated into the central platform of the project available for the advanced and common users interested in fiscal data analysis. The pilot analysis showed that the problem of data mining in this domain is the large amount of found rules together with its heterogenous origin.

Security tips are now used as a method of priming online users from falling prey for fraudulent scams. These security tips usually come as email, SMS or online posts where they can be easily accessed by the users. In this work, phishing attacks are simulated with varying cues that are available in such fraudulent email messages, SMS and web pages were used to investigate the effectiveness of the security tips used by Nigerian banks to prime their customers of online threats. A total of 427 respondents, purposively selected from three tertiary institutions in Ogun State, participated in the study. Each respondent was asked to identify five messages with varying phishing cues to evaluate their understanding of the security tips messages. The results which were computed at 95% Confidence Interval, indicated that 58.91% failed on the first attribute, 58.59% failed on the second attribute while 58.73% failed on the third attribute. 74.24% of the participant could not correctly identify a fake email message (fourth attribute) while 76.71% could not correctly identify a phished bank verification number update message (fifth attribute). Using the Mann Whitney Test, the result further showed that overall, those who failed the test are significantly more than those who passed. Moreover, a regression model is proposed to evaluate the influence of the socio demographic factors used in the study. This result indicated that gender, academic qualification and user's computer knowledge significantly influences their ability to recognize phished messages.

The paper examines effects of a predefined and immutable money supply using a simulation performed in Minsky. It uses the cryptocurrency Bitcoin as an example and compares its settings and outcomes with Euro as a credit based fiat currency. Minsky is a specialized software for creating SFC economic models. It operates in continuous time. Unlike Euro, Bitcoin is a non-liability currency. It is not being issued against debt and it does not allow a fiduciary issue. The study examines the economy of the EU complexly, focusing on its monetary system, using Eurostat data. Then it changes the rules of the system so that they comply with the rules of Bitcoin’s protocol. The performed simulations show different effects of these monetary settings on wealth distribution among particular groups of economic subjects as well as on the stability of the economy as a whole after some time has passed.

In this paper we describe a case where the top management of a small holding company is involved in a love-hate relationship with its own IT department. The top management firmly believes that IT staff is involved in leaking out company's secrets. However, having no expertise in IT and even lesser grasp on the complexity of IT architecture resulting from recent mergers and acquisition, the top management finds itself crucially dependent on its IT systems, yet unable to trust them fully. The theories of deterrence and reasoned action are used to explain the otherwise objectionable behaviour of the perpetrator.

This article aims to provide a brief and comprehensive introduction to the issue of cyber warfare and to display the recent development in this area. Geographically, it focuses on the Middle East region, since the vast majority of the most important recent cyber attacks appeared just in there or were connected to it. The first part of the article tries to define the key notion of cyber warfare, compares it to the standard warfare and presents different types of cyber weapons that are known today. The second part points out examples of the most striking recent cyber attacks and uses them as evidences to demonstrate today's importance and dissemination of cyber warfare. Finally, the article sums up pros and cons of the cyber weapons and, in view of these, predicts a significant increase in their use in any future war conflicts.

With the thriving technology and the great increase in the usage of computer networks, the risk of having these network to be under attacks have been increased. Number of techniques have been created and designed to help in detecting and/or preventing such attacks. One common technique is the use of Intrusion Detection Systems (IDS). Today, number of open sources and commercial IDS are available to match enterprises requirements. However, the performance of these systems is still the main concern. This paper examines perceptions of intrusion detection architecture implementation, resulting from the use of graphics processor. It discusses recent research activities, developments and problems of operating systems security. Some exploratory evidence is presented that shows capabilities of using graphical processors and intrusion detection systems. The focus is on how knowledge experienced throughout the graphics processor inclusion has played out in the design of intrusion detection architecture that is seen as an opportunity to strengthen research expertise.