- Leadership in project management: a scoping review
- Emotional intelligence and success of project management: the mediating effect of interpersonal skills
- Ethical challenges during construction project handovers
- Critical factors for benefits realisation in collaborative university-industry R&D programs
7 May 2021
Free sample articles newly available from International Journal of Project Organisation and Management
- Social protection floors as an investment in the future
- EU economic governance and the COVID-19 crisis: between path-dependency and paradigmatic shift
- 'Building back better': social justice in the green economy
- How Covid-19 post-recovery plans can tackle poverty and address economic inequality in the USA
- The idea of a human rights-based economic recovery after COVID-19
Free sample articles newly available from International Journal of Manufacturing Technology and Management
- Optimal design of flux for submerged arc weld properties based on RSM coupled with GRA and PCA
- Investigation on turning parameters on machining time and vibration of carbon fibre reinforced laminates
- Cellular layout formation by using weighted similarity-based modified flow matrix with process sequence data
- Active acquisition system of LBS-based logistics freight source information
- One size does not even fit one: supply chain strategies in the decline phase
- Investigation of HFRC beams retrofitted using GFRP for enhancement in flexural capacity
6 May 2021
Special issue published: "Artificial Intelligence and Technology Diffusion – Multinational Marketing Management Strategies"
- The role of multinational technology companies in facilitating emerging enabling technologies for industry transformation: the case of artificial intelligence in intelligent manufacturing in Taiwan
- Media richness and adoption intention of voice assistants: a cross-cultural study
- Factors influencing foreign consumers to adopt mobile payment extensions offered by multinational mobile messaging applications
- Multinational enterprises' subsidiary initiative-taking: a model for implementing corporate social responsibility
Free sample articles newly available from International Journal of Information and Operations Management Education
- Decomposing bills of materials using the Gozinto-list-method
- Benefits of self-selected projects from students' workplace as a pedagogical tool in graduate operations management classes
- Information systems freshmen teaching: case experience from day one
- Using transactional distances to explore student satisfaction with group collaboration in the flipped classroom
- Teaching data envelopment analysis in production operations management through an undergraduate research project based on real-world data
- Sales and operations planning spreadsheet homework
Free open access article available: "Is benzoyl peroxide detectable under physiological conditions in orthopaedic cement?"
The following paper, "Is benzoyl peroxide detectable under physiological conditions in orthopaedic cement?" (International Journal of Nano and Biomaterials 10(1) 2021), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Research pick: Blurred lines in face recognition - "Face spoofing detection using improved SegNet architecture with a blur estimation technique"
Face recognition has come on apace from a cliched trope of science fiction to a reality of the modern world with widespread use in photography databases, social media, and the security world. However, as with any tool, there are those who would abuse it for nefarious ends. New research published in the International Journal of Biometrics investigates one such aspect of face recognition where a third party might “spoof” the face of a legitimate user to gain access to systems and services to which they are not entitled and offers a suggestion as to how such spoofing might be detected.
Sandeep Kumar, Sukhwinder Singh, and Jagdish Kumar of the Punjab Engineering College in Chandigarh, India, explain how biometrics, including face recognition, has come to the forefront of security in all sorts of realms from the simple accessing of a person’s smartphone to securing sensitive premises. The key to precluding face recognition spoofing lies in the determination of whether the face being presented to the security camera or device is “live” or a static photograph or video rather than the actual person.
The team has turned to an improved SegNet-based architecture that can measure “blur” on the basis of local minimum and maximum left and right edges and calculate blur of horizontal and vertical edges. A flat image such as a photograph or video display presented to a security camera or device would be wholly in focus whereas “depth-of-field” comes into play. With a three-dimensional object, such as a real face, presented to the camera, the eyes would be sharply in focus assuming the camera focused on that part of the face, but the curved sides of the head would be slightly out of focus because they are not in the same plane relative to the camera lens as the eyes. Regardless, it is technically impossible for the whole of a three-dimensional object presented to a camera to be in focus, detecting the blur of parts of the object in front of or behind the focal plane is key to discerning whether a real face is in front of the camera or a flat image.
The team’s proof of principle offers up to 97 percent accuracy, which is an improvement on earlier algorithms when tested against standard benchmarks. Moreover, it can determine the “liveness” of a presented face within about one second. The researchers are now working on improving their system’s speculation abilities by looking at shading, another characteristic of a real face that is is obvious to a person looking at a face but difficult for a computer to detect via a camera.
Kumar, S., Singh, S. and Kumar, J. (2021) ‘Face spoofing detection using improved SegNet architecture with a blur estimation technique’, Int. J. Biometrics, Vol. 13, Nos. 2/3, pp.131–149.
5 May 2021
- Efficient data clustering algorithm designed using a heuristic approach
- Bayesian consensus clustering with LIME for security in big data
- Semantic integration of traditional and heterogeneous data sources (UML, XML and RDB) in OWL2 triplestore
- Sentiment classification of review data using sentence significance score optimisation
- Evaluating information criteria in latent class analysis: application to identify classes of breast cancer dataset
- Improving social media engagements on paid and non-paid advertisements: a data mining approach
- Towards knowledge warehousing: application to smart housing
- Road signs recognition: state-of-the-art and perspectives
- Combining planning and learning for context aware service composition
Free sample articles newly available from International Journal of Business Performance and Supply Chain Modelling
- The influence of greening the suppliers on environmental and economic performance
- Hybrid SEM-neural networks for predicting electronics logistics information system adoption in Thailand healthcare supply chain
- Production and distribution scheduling optimisation in a three-stage integrated supply chain using genetic algorithm
- Green supply chain management: learning from Indian chemical sector
- Performance analysis of a PCM integrated domestic solar water heater by numerical simulations
- A review on performance, heat transfer and exergy analysis of solar flat plate collectors
- One step low temperature synthesis of poly vinyl alcohol stabilised α-Ni (OH)2 nanoparticles - structural, morphological and optical studies
- The review and investigation of sustainable 13-level multilevel inverter control strategies
- Composites materials for sustainable space industry: a review of recent developments
- Investigation on metallurgy and material strength enhancement of 20MnCr5 forged link chain in cement mill
- Prediction of solids outlet moisture content in a continuous wall heated fluidised bed dryer for uniform and binary solid mixtures
- A novel hybrid approach to blaze out a new path for glaucoma detection, monitoring and sustainable results in fundus images
- Sustainable analysis of liver tumour detection using various segmentation techniques
- Experimental studies on treatment of wastewater using Cladophora sp. and advanced oxidation
- Structural and compositional evaluation of waste cooking oil-algal oil biodiesel using FTIR and GC-FID for improved fuel properties
- A comprehensive literature survey for deep learning approaches to agricultural applications
Research pick: Using “ant colonies” to find fake news - "An ant colony optimisation-based framework for the detection of suspicious content and profile from text corpus"
Although it might be said that there has been malicious writing since our ancestors daubed cave walls with ochre symbols or the very first scribes notched letters into ancient stone tablets, fake news, spam, malicious and threatening words have come to the fore with the advent of our ubiquitous and always-connected digital devices. We might refer to this as “suspicious content”.
New work published in the International Journal of Intelligent Systems Technologies and Applications, developed an optimisation framework for detecting suspicious content in a body of text. The algorithm is built on a biological paradigm – the behaviour of an ant colony.
The individual members of an ant colony carry out tasks and use pheromones to communicate with other members of the colony. They can solve rather complex problems together even though the individual ants lack the cognitive skills to do so. In computer science, the way in which individual ants behave, each acting as an agent in a problem “space”, can be modelled in an ant colony optimization algorithm (ACO). This probabilistic technique simulates the way in which the colony finds solutions to problems such as finding and transporting food via the shortest and safest route from food source to the colony’s food store and many other colony activities. Previously, vehicle and internet routing problems have been solved using ACO, but the same approach can be applied to finding solutions to other problems such as detecting patterns of words in a large text corpus, for instance.
Asha Kumari and Balkishan of the Department of Computer Science and Applications at Maharshi Dayanand University in Rohtak, India, have focused on mobile phone text message content (short messaging service, SMS) and updates on the well-known microblogging social media platform Twitter. Given the ubiquity of these services in everything from entertainment, internet banking, navigation, trading, and other services requiring short messages, it is important to have tools to hand to quickly and accurately detect suspicious content.
Kumari, A. and Balkishan (2021) ‘An ant colony optimisation-based framework for the detection of suspicious content and profile from text corpus’, Int. J. Intelligent Systems Technologies and Applications, Vol. 20, No. 1, pp.1–24.
- Investigation on microstructures and phases of Fe-Ga alloy films deposited by magnetron sputtering
- Polysaccharide capped antibacterial silver nanoparticles synthesis using green chemistry
- All optical four bit two's complement generator and single bit comparator using reflective semiconductor optical amplifier
- Controlled hardware architecture for fractal image compression
- Strain engineering in AlGaN/GaN HEMTs for performance enhancement
- Role of stress/strain mapping and random dopant fluctuation in advanced CMOS process technology nodes
- Extended nucleic acid memory as the future of data storage technology
There’s an app for that…but which one to choose?
The growth of software – colloquially known as apps, meaning applications – for mobile devices such as smart phones and tablet computers has been enormous. Well-known apps are easy to find or users learn of them through word-of-mouth. However, searching for a previously unknown app that perfectly fits one’s needs is not always straightforward.
Now, writing in the International Journal of Intelligent Information and Database Systems, a team from Algeria and France have developed a new approach to searching for apps that homes in on the functionality the user needs by mining not only the app’s description but also the reviews left by users. The team’s approach then scores the results offering the user the most relevant app to match their needs. The team describes their proof of principle as effective and able to perform better than the state-of-the-art retrieval models for app retrieval.
Messaoud Chaa of the University of Bejaia and the Research Center on Scientific and Technical Information, CERIST, colleague CERIST colleague Omar Nouali, Algeria and Patrice Bellot of Aix Marseille University, France, explain that there were around 30 billion app downloads in 2019 and this number is growing with growing smartphone and tablet adoption around the world. In the Google Play Store alone there are almost 3 million apps, while the Apple App Store carries more than 2 million. “An efficient app search system is essential”, the team writes and at the present time, there is no perfect tool for searching for the app you need that you don’t know exists.
The team’s approach using natural language processing (NLP) allows them to obtain a score for each app and its functions that can be searched by the prospective user and matched more precisely to their needs than a simple app name search might offer.
Chaa, M., Nouali, O. and Bellot, P. (2021) ‘Leveraging app features to improve mobile app retrieval’, Int. J. Intelligent Information and Database Systems, Vol. 14, No. 2, pp.177–197.
A new video equivalent of optical character recognition (OCR) but for sign language is described by researchers from China in the International Journal of Systems, Control and Communications.
Kai Zhao, Daotong Wang, and Jianbo Su of Shanghai Jiao Tong University and Kejun Zhang and Yu Zhai of the Shanghai Lingzhi High-Tech Corporation discuss a system that can recognise Chinese sign language in a video stream and convert the language in real-time into text. Such a system could be used to automate the generation of subtitles for people sharing the video stream who are not familiar with Chinese sign language. The system was built with a database of half a million video segments and uses a three-dimensional convolutional neural network to extract the relevant frames for conversion.
This is, the team writes, “a complete real-time sign language recognition system” for Chinese sign language. It is composed of a human interaction interface, a motion detection module, a hand and head detection module, and a video acquisition mechanism. The researchers have now demonstrated 92.6% recognition accuracy on a dataset containing 1,000 vocabularies. The system would not only be useful in adding captions to video of a signer but could be used in public areas such as hospitals, banks, and train stations where a person signing could talk to a member of staff who is a non-signer for instance.
The team adds that improvements to the accuracy of the system might be made by incorporating skin detection to extract greater subtleties from the movements of the person signing. Likewise, the addition of detection of the signers underlying skeleton would also add to the sophistication of the recognition system and so improve accuracy.
Zhao, K., Zhang, K., Zhai, Y., Wang, D. and Su, J. (2021) ‘Real-time sign language recognition based on video stream’, Int. J. Systems, Control and Communications, Vol. 12, No. 2, pp.158–174.
4 May 2021
Free sample articles newly available from International Journal of Data Analysis Techniques and Strategies
- Hybrid fuzzy logic and gravitational search algorithm-based multiple filters for image restoration
- Bayesian feature construction for the improvement of classification performance
- A novel ensemble classifier by combining sampling and genetic algorithm to combat multiclass imbalanced problems
- Dynamics of the network economy: a content analysis of the search engine trends and correlate results using word clusters
- Face spoofing detection using improved SegNet architecture with a blur estimation technique
- Image recognition method for fault service action of tennis based on feature matching
- A gait recognition method for a moving target image in sports based on a decision tree
- Target tracking and recognition of a moving video image based on convolution feature selection
- Feature extraction method of face image texture spectrum based on a deep learning algorithm
- An analysis of Mandarin emotional tendency recognition based on expression spatiotemporal feature recognition
- Research on emotion recognition method of weightlifters based on a non-negative matrix decomposition algorithm
- The method of table tennis players' posture recognition based on a genetic algorithm
- Improvement of a face recognition method for high jumper with a single sample based on Lucas-Kanade algorithm
- Feature similarity measurement of cross-age face images based on a deep learning algorithm
- Multi-view face pose recognition model construction based on a typical correlation analysis algorithm
- Recognition algorithm of athletes' partially occluded face based on a deep learning algorithm
- Multi-scale neighbourhood based-tree binary pattern: a new feature descriptor for face recognition
- Proposition of new secure data communication technique based on Huffman coding, chaos and LSB
Free sample articles newly available from International Journal of Service and Computing Oriented Manufacturing
- A big data services platform framework towards cloud manufacturing system
- Multi-objective machining parameter optimisation for residual stress based on quantum cat swarm
- Smart factory and education: an integrated automation concept
- Advanced planning and scheduling system with application in the tobacco industry
- A protégé semantic modelling approach for combination correlation of manufacturing service
- MIMO wireless power transfer based on magnetic beamforming
30 April 2021
Special issue published: "Advances in Machine Learning and Intelligent Systems – Challenges and Solutions"
- Demographical gender prediction of Twitter users using big data analytics: an application of decision marketing
- Energy efficient task scheduling using adaptive PSO for cloud computing
- Deep learning-based detection and prediction of trending topics from streaming data
- NITCO: an intelligent agent technique for optimising of resource utilisation in cloud
- A novel approach for dynamic information integration
- Utilising predictive analytics for decision-making and improving healthcare services in public maternal healthcare database
- Computing semantic relatedness using latent semantic analysis and fuzzy formal concept analysis
- Adaptive edge-based bi-cubic image interpolation
- Deep convolutional neural network-based diabetic eye disease detection and classification using thermal images
Free sample articles newly available from International Journal of Intelligent Systems Technologies and Applications
- A novel and improved developer rank algorithm for bug assignment
- Meta-heuristic techniques for path planning: recent trends and advancements
- Design of generalised predictive controller for dynamic positioning system of surface ships
- Detection of glaucoma based on cup-to-disc ratio using fundus images
- Machine transliteration using SVM and HMM
- SPIDER-based out-of-order execution scheme for Ht-MPSOC
- An efficient pattern matching approach using double measures of correlation and rank reduction
- Modified FPred-Apriori: improving function prediction of target proteins from essential neighbours by finding their association with relevant functional groups using Apriori algorithm
- A new image binarisation technique for segmentation of text from digital images
- Metaheuristics-based routing optimisation, balanced workload distribution and security strategy in IoT environment
Research pick: Stockmarkets in the time of covid - "Examining the impact of coronavirus on stock markets: investigating the cointegration and transmission of shocks between China and the world’s largest stock markets"
A new study in the International Journal of Business and Emerging Markets looks at how the beginning of the COVID-19 pandemic affect stockmarkets in China and how the “shocks” experienced there were transmitted to the world’s largest stockmarkets.
Naveed Ul Haq and Abid Shirwani of the University of Management and Technology in Lahore, Pakistan, used a wide range of analytical tools to examine the ebb and flow of value in the long-run and short-term over the period January 2012 to March 2020, which culminated in the announcement of a global pandemic. The tools included unit root test, Johansen cointegration test, vector error correction model, Granger causality test, variance decomposition, and impulse response function test.
The team observed long-run relationships between stock markets and could clearly see short-run results showing that the previous day’s stock prices in Hong Kong and the US had a positive relationship with the Chinese stockmarket. The Granger causality results, however, showed something different – a unidirectional long-run causality from the UK, Hong Kong and Japan to China. In the short-run causality results the effects are bidirectional between China and the world’s major stockmarkets.
The team explains how their findings support the well-known prospect theory or loss-aversion theory, whereby investors are generally more afraid of loss then they are encouraged by a gain. This means that given a choice of two different prospects, investors will generally choose the one that has less chance of ending in a loss rather than the one that offers more gains. In terms of the COVID-19 crisis, the study suggests that it was not the socioeconomic circumstances prior to the pandemic that influenced stockmarket reactions but rather the health policies implemented during the crisis that had the most impact.
Ul Haq, N. and Shirwani, A.H.K. (2021) ‘Examining the impact of coronavirus on stock markets: investigating the cointegration and transmission of shocks between China and the world’s largest stock markets’, Int. J. Business and Emerging Markets, Vol. 13, No. 2, pp.206–232.
29 April 2021
- T-S fuzzy observers design and actuator fault tolerant control applied to vehicle lateral dynamics
- Solar integrated combined cooling-power generation systems for waste heat recovery using different energy efficient materials
- Robust integral sliding mode controller design of a bidirectional DC charger in PV-EV charging station
- A summary study on handwritten documents' word spotting
- Numerical approach for parameter extraction of a photovoltaic module based on datasheet and five parameters model
- Fault detection and isolation using sliding mode observers with sensor fault in robot manipulator
- Testing and simulation of a solar PV/battery storage system with and without PWM charge control
- Effect of some operational conditions on bioelectricity production in algal fuel cell Free access
- Enhancing the performance of a building integrated compound parabolic photovoltaic concentrator using a hybrid photovoltaic cell
- Contribution to the reliability study of photovoltaic systems using static and dynamic analysis methods
- Renewable energy investment prospects in Turkey's power generation sector
International Journal of Powertrains to invite expanded papers from International Conference on Advanced Vehicle Powertrains (ICAVP2021) for potential publication
Research pick: Women entrepreneurs in STEM - "STEM educated women entrepreneurs in Denmark, Latvia and Turkey: a context-based explorative study"
A new study from researchers in Denmark and Germany suggests that despite the growing number of women entrepreneurs, numbers in the STEM (science, technology, engineering, and mathematics) are now adequately represented in this trend. Details of an exploratory study across Denmark, Latvia, and Turkey, are reported in the International Journal of Entrepreneurial Venturing, and hope to explain this underrepresentation in STEM.
Sanita Ármane, Seda İrem Gärtig, and Silke Tegtmeier of the University of Southern Denmark, in Sønderborg and Alexander Brem of the University of Stuttgart, carried out interviews with a number of women entrepreneurs educated in STEM subjects. They uncovered the women’s main motivations, the challenges they face, and the support sources on which they rely to glean important advice for future women entrepreneurs as well as for policymakers to increase the number of STEM-educated women entrepreneurs at the national level.
A recent survey across Europe revealed that only about a third of all the millions of entrepreneurs in the business world are women. This reinforced the long-standing notion that entrepreneurship is a male-dominated field. Moreover, the underrepresentation of women from a STEM background is also rather worrying with most companies run by women not being involved in those areas. Reinforcing a second notion that businesses founded in STEM areas tend to be male-dominated too.
Many observers have argued that encouraging more women entrepreneurs in STEM-related fields is of great importance in terms of economic growth and an enhancing social status. Moreover, gender diversity at the top of any corporate hierarchy is key to ensuring the diversity of employees, again all to the positive in terms of socioeconomic benefits.
This new study points to possible reasons for the shortfall in the number of women entrepreneurs from a STEM background and running businesses that work in the areas covered by STEM. The work shows the apparent differences across three nations and offers new advice on how women from a STEM background might be encouraged to seek out and exploit new opportunities as entrepreneurs.
Ármane, S., Gärtig, S.I., Tegtmeier, S. and Brem, A. (2021) ‘STEM educated women entrepreneurs in Denmark, Latvia and Turkey: a context-based explorative study’, Int. J. Entrepreneurial Venturing, Vol. 13, No. 2, pp.186–216.
28 April 2021
Special issue published: "Machine Learning, Artificial Intelligence and Big Data: Methods and New Perspectives for Research and Society"
- Depth-based support vector classifiers to detect data nests of rare events
- Automated detection of entry and exit nodes in traffic networks of irregular shape
- Does time-frequency scale analysis predict inflation? Evidence from Tunisia
- A SAS macro for examining stationarity under the presence of endogenous structural breaks
Free sample articles newly available from International Journal of Internet Manufacturing and Services
The following sample articles from the International Journal of Internet Manufacturing and Services are now available here for free:
- Factors affecting users' stickiness in online car-hailing platforms: an empirical study
- Analysis of scientific and technological innovation influence factors affect enterprise performance
- Research and analysis on sensitive data encryption method in accounting information processing system
- Multi-source remote sensing image big data classification system design in cloud computing environment
- Reliability in IoUT enabled underwater sensor networks using dynamic adaptive routing protocol
- Trust-based fruit fly optimisation algorithm for task scheduling in a cloud environment
- Outlier data mining of multivariate time series based on association rule mapping
- Research on virus diffusion prevention method for computer singularity in complex sensor networks
- Research on algorithm of information transmission path planning in big data environment
- The information security scheduling method of vehicle self-organising system for wireless sensor
- Mobile self-organising network positioning algorithm based on node clustering
- Design of candidate schedules for applying iterative ordinal optimisation for scheduling technique on cloud computing platform
- PPHE-automatic detection of sensitive attributes in a privacy preserved Hadoop environment using data mining techniques
- SIBLAR: a secured identity-based location aware routing protocol for MANETs
- Divide-by-16/17 dual modulus prescaler design with enhanced speed in a 180nm CMOS technology
- IoT-enabled traffic sign recognition for safe driving
- A hybrid SATS algorithm-based optimal power flow for security enhancement using SSSC
- HUPM-MUO: high utility pattern mining under multiple utility objectives
- A hybrid approach to diagnosis mammogram breast cancer using an optimally pruned hybrid wavelet kernel-based extreme learning machine with dragonfly optimisation
- Hardware implementation of a modified SSD LDPC decoder
- Spur gear safety prediction through the analysis of stress intensity factor
In this Research Pick, we are highlighting three papers from the International Journal of Web Based Communities that focus on how social media has responded to the COVID-19 pandemic in this time of worldwide crisis.
The first paper discusses how social media and web-based communities in general have responded to the pandemic whereby small groups of worshippers almost overnight converted their usual activities to the online world without much need for intervention from the hierarchy above, as it were. The second offers a personal perspective on the pros and cons, the benefits and challenges of social networking during the pandemic. Finally, the third paper looks at how faith communities have moved online to allow their congregations to continue with their religious endeavours.
The emergence of a novel coronavirus, dubbed SARS-CoV-2, in late 2019 and its subsequent spread around the world leading to the declaration of the disease it causes, COVID-19, as a pandemic led to many changes in the daily lives of billions of people. Of course, there is the ongoing tragedy of those who suffer serious symptoms and in many cases death, and there is also the ongoing problem of so-called Long-covid, symptoms that seem to persist long after the person has stopped being infectious, such as severe fatigue and significant disruption or loss of one’s sense of smell.
The socioeconomic symptoms of this pandemic have seen enormous changes in working practices, closure of many areas of normal life such as entertainment and hospitality, the disruption of sporting events, and more significantly the failure of many companies and enterprises and lost jobs for those affected.
We are yet to fully understand what detrimental impact this disease will have on humanity and at the time of writing, new waves of infections underpinned by new, lethal variants of the disease, are overwhelming healthcare systems in Brazil, India, and elsewhere. Many parts of the world remain in lockdown while others that have escaped the worst ravages so far are keeping a weather eye on their borders in the hope of precluding the spread of a new variant in their country.
The role of social media for the spread of information about COVID-19, vaccination programs, and public awareness of lockdown rules may well have helped reduce the total number of infections and deaths from the earliest and potentially devastating predictions. Moreover, social media and its attendant applications, including video conferencing, have allowed many people to continue their work and maintain family and social connections online in a way that would not be possible without this technology.
There has been a downside to the so-called “new normal” for many, especially those on the wrong side of the digital divide that have no reliable access to the requisite devices and high-speed internet connections needed to make the most of social media and video conferencing and the like. Even for those with access to the necessary tech, the downside of living one’s working life and social life almost exclusively online has exacted a toll on mental health for many people trapped behind a screen and unable to fulfil their old-normal roles in life.
All three papers cited below will appear in IJWBC soon.
Isaias, P., Miranda, P. and Pifano, S. (2021) ‘Framing social media and web-based communities within the COVID-19 pandemic: enduring social isolation and subsequent deconfinement’, Int. J. Web Based Communities, Vol. 17, No. 2, pp.120–134.
Issa, T., Al Jaafari, M., Alqahtani, A.S., Alqahtani, S., Issa, T., Maketo, L. and Pervaiz, S. (2021) ‘Benefits and challenges of social networking during COVID-19: personal perspective’, Int. J. Web Based Communities, Vol. 17, No. 2, pp.135–148.
Cooper, A-P., Jormanainen, I., Shipepe, A. and Sutinen, E. (2021) ‘Faith communities online: Christian churches’ reactions to the COVID-19 outbreak’, Int. J. Web Based Communities, Vol. 17, No. 2, pp.99–119.