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Online question-and-answer (Q&A) communities serve as important channels for knowledge diffusion. The purpose of this study is to investigate the dynamic development process of online knowledge systems and explore the final or progressive state of system development. By measuring the nonlinear characteristics of knowledge systems from the perspective of complexity science, the authors aim to enrich the perspective and method of the research on the dynamics of knowledge systems, and to deeply understand the behavior rules of knowledge systems.

The authors collected data from the programming-related Q&A site Stack Overflow for a ten-year period (2008–2017) and included 48,373 tags in the analyses. The number of tags is taken as the time series, the correlation dimension and the maximum Lyapunov index are used to examine the chaos of the system and the Volterra series multistep forecast method is used to predict the system state.

There are strange attractors in the system, the whole system is complex but bounded and its evolution is bound to approach a relatively stable range. Empirical analyses indicate that chaos exists in the process of knowledge sharing in this social labeling system, and the period of change over time is about one week.

This study contributes to revealing the evolutionary cycle of knowledge stock in online knowledge systems and further indicates how this dynamic evolution can help in the setting of platform mechanics and resource inputs.

The purpose of this paper is to investigate longitudinal features of an established social question-answering (Q&A) site to study how question-answer resources and other community features change over time.

Statistical analysis and visualisation was performed on the full data dump from the Stack Overflow social Q&A site for programmers.

The timing of answers is as strong a predictor of acceptance – a proxy for user satisfaction – as the structural features of provided answers sometimes associated with quality. While many questions and answer exchanges are short-lived, there is a small yet interesting subset of questions where new answers receive community approval and which may end up being ranked more highly than early answers.

As a large-scale data oriented research study, this work says little about user motivations to find and contribute new knowledge to old questions or about the impact of the resource on the consumer. This will require complementary studies using qualitative and evaluative methods.

While content contribution to social question-asking is largely undertaken within a very short time frame, content consumption is usually over far longer periods. Methods and incentives by which content can be updated and maintained need to be considered. This work should be of interest to knowledge exchange community designers and managers.

Few studies have looked at temporal patterns in social Q&A and how time and the moderation and voting systems employed may shape resource quality.

The purpose of this paper is to explore to which extent the quality of social media short text without extensions can be investigated and what are the predictors, if any, of such short text that lead to trust its content.

The paper applies a trust model to classify data collections based on metadata into four classes: Very Trusted, Trusted, Untrusted and Very Untrusted. These data are collected from the online communities, Genius and Stack Overflow. In order to evaluate short texts in terms of its trust levels, the authors have conducted two investigations: (1) A natural language processing (NLP) approach to extract relevant features (i.e. Part-of-Speech and various readability indexes). The authors report relatively good performance of the NLP study. (2) A machine learning technique in more precise, a random forest (RF) classifierusing bag-of-words model (BoW).

The investigation of the RF classifier using BoW shows promising intermediate results (on average 62% accuracy of both online communities) in short-text quality identification that leads to trust.

As social media becomes an increasingly new and attractive source of information, which is mostly provided in the form of short texts, businesses (e.g. in search engines for smart data) can filter content without having to apply complex approaches and continue to deal with information that is considered more trustworthy.

Short-text classifications with regard to a criterion (e.g. quality, readability) are usually extended by an external source or its metadata. This enhancement either changes the original text if it is an additional text from an external source, or it requires text metadata that is not always available. To this end, the originality of this study faces the challenge of investigating the quality of short text (i.e. social media text) without having to extend or modify it using external sources. This modification alters the text and distorts the results of the investigation.

In the co-creation process from a network perspective, service is produced, designed, and evaluated entirely by the actors with dynamic roles and with less participation by the firm's employees in the service process. The purpose of this paper is to develop a theoretical model that represents environmental stimuli and value perceptions that contribute to service co-creation behaviour in an online network.

A total of 36 semi-structured interviews were conducted with members of two online programming communities – GitHub and Stack Overflow co-creators, with the data analysed using thematic analysis. The stimulus-organism-response model guided the development of the final model.

Social influence and trust are influential in actor value perceptions, including primary and network value, the interplay of which leads actors to co-production, supportive, and administrative behaviour. Environmental factors do not directly drive actors; rather it is the value that initiates and drives actors, which, by extension, initiates and drives the co-creation of services.

The service co-creation behaviour model provides a basis for future research in the co-creation and co-destruction context to model behaviours within the online network organisation setting and thereby enable improvement of such systems. This model can be operationalised in a network environment through design features.

This paper provides a rich understanding of environmental stimuli and value perception factors that contribute to the co-creation of services, and identifies different types of behaviours in dynamic online networks. This paper presents a new model of different types of behaviours emerging from actor participation in the co-creation process.

Social question and answer (SQA) site is one of the factors that boosted up and popularized the vision of social web. It enables community members to post highly valued answers to globally asked questions and information seekers to grab intellectual information in a contextual, concise, and meaningful format at the cost of investing a few minutes. The purpose of this paper is to present a common architecture, history, and a comprehensive review of such sites.

A critical and analytical investigation of the state-of-the-art SQA sites and relevant literature has been carried out with the intention to explore the noticeable features of such sites.

By studying relevant literature, and analysing a number of existing systems, a number of research challenges are identified and a generic architecture of SQA sites is contributed.

The review contributes a comprehensive knowledge about SQA systems and aims to be helpful to new researchers who want to get a broad picture of SQA systems on a single platform. The domain is in its infancy and requires tremendous efforts from the research community to explore its salient aspects with respect to the human world.

The study inspects SQA sites on a large scale and makes an original contribution by presenting a comprehensive review, future research challenges, and a generic architecture of SQA sites.

This study aims to investigate the nature and evolution of online communities in the early stages of their life cycles. The authors analyze the topics of discussions in an online community to identify issues related to community development. The authors also compare the topics of exemplary questions that founding members believed to be asked with the real questions based on members' information needs.

The authors use Medical Sciences Stack Exchange, a health Q&A community of Stack Exchange, which requires four stages of development: definition, commitment, private beta and public beta. The authors collect postings of discussions and health questions in the first three stages, perform a content analysis of the postings and analyze the topics of discussions and health questions.

The authors find that the topics of discussions evolved dynamically with the issues of community governance, role as a medical/health community, members and roles, content management, quality control and community design. The authors also find that the real questions included more specific and diverse issues than the exemplary questions that founding members expected.

Theoretically, this study tests the community life cycle model in an online community that has explicit phase markers. The findings could shed light on community development and help prioritize issues to solve and decisions to make in its early stages. Additionally, this study focuses on the challenges and concerns in online health community building and solutions generated by collective efforts that could influence health communications in online communities.

Internet has changed radically in the way people interact in the virtual world, in their careers or social relationships. IoT technology has added a new vision to this process by enabling connections between smart objects and humans, and also between smart objects themselves, which leads to anything, anytime, anywhere, and any media communications. IoT allows objects to physically see, hear, think, and perform tasks by making them talk to each other, share information and coordinate decisions. To enable the vision of IoT, it utilizes technologies such as ubiquitous computing, context awareness, RFID, WSN, embedded devices, CPS, communication technologies, and internet protocols. IoT is considered to be the future internet, which is significantly different from the Internet we use today. The purpose of this paper is to provide up-to-date literature on trends of IoT research which is driven by the need for convergence of several interdisciplinary technologies and new applications.

A comprehensive IoT literature review has been performed in this paper as a survey. The survey starts by providing an overview of IoT concepts, visions and evolutions. IoT architectures are also explored. Then, the most important components of IoT are discussed including a thorough discussion of IoT operating systems such as Tiny OS, Contiki OS, FreeRTOS, and RIOT. A review of IoT applications is also presented in this paper and finally, IoT challenges that can be recently encountered by researchers are introduced.

Studies of IoT literature and projects show the disproportionate importance of technology in IoT projects, which are often driven by technological interventions rather than innovation in the business model. There are a number of serious concerns about the dangers of IoT growth, particularly in the areas of privacy and security; hence, industry and government began addressing these concerns. At the end, what makes IoT exciting is that we do not yet know the exact use cases which would have the ability to significantly influence our lives.

This survey provides a comprehensive literature review on IoT techniques, operating systems and trends.

The purpose of this paper is to propose a self‐immune automated signature generation (SISG) for polymorphic worms which is able to work well, even while being attacked by any types of malicious adversary and produces global‐suited signatures other than local‐suited signatures for its distributed architecture. Through experimentations, the method is thereafter evaluated.

The ideal worm signature exist in each copy of the corresponding worm, but never in other worm categories and normal network traffic. SISG compares each worm copy and extract the same components, then produces the worm signature from the components which must achieve low‐false positive and low‐false negative. SISG is immune from the most attacks by filtering the harmful noise made by malicious adversaries before signature generation.

NOP sled, worm body and descriptor are not good to be signature because they can be confused intricately by polymorphic engines. Protocol frames may not suit to be signature for the anti‐automated signature generation attacks. Exploit bytes is the essential part of an ideal worm signature and it can be extracted by SISG exactly.

The paper proposes a SISG for polymorphic worms which is able to work well even while being attacked by any types of malicious adversary and produces global‐suited signatures other than local‐suited signatures for its distributed architecture.

This paper aims to make it convenient for those who have only just begun their research into Community Question Answering (CQA) expert recommendation, and for those who are already concerned with this issue, to ease the extension of our understanding with future research.

In this paper, keywords such as “CQA”, “Social Question Answering”, “expert recommendation”, “question routing” and “expert finding” are used to search major digital libraries. The final sample includes a list of 83 relevant articles authored in academia as well as industry that have been published from January 1, 2008 to March 1, 2019.

This study proposes a comprehensive framework to categorize extant studies into three broad areas of CQA expert recommendation research: understanding profile modeling, recommendation approaches and recommendation system impacts.

This paper focuses on discussing and sorting out the key research issues from these three research genres. Finally, it was found that conflicting and contradictory research results and research gaps in the existing research, and then put forward the urgent research topics.