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Young people frequently make use of the internet as part of their day-to-day activities, and this has extended to their help-seeking behavior. Offline help-seeking is known to be impeded by a number of barriers including stigma and a preference for self-reliance. Online help-seeking may offer an additional domain where young people can seek help for mental health difficulties without being encumbered by these same barriers. The objective of this systematic literature review was to examine young peoples' online help-seeking behaviors for mental health concerns. It aimed to summarize young peoples' experiences and identify benefits and limitations of online help-seeking for this age group. It also examined the theoretical perspectives that have been applied to understand online help-seeking. A systematic review of peer-reviewed research papers from the following major electronic databases was conducted: PsycINFO, Cumulative Index of Nursing and Allied Health Literature, PubMed, Cochrane Library, Association for Computing Machinery Digital Library, and Institute of Electrical and Electronics Engineers Xplore. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. The search was conducted in August 2017. The narrative synthesis approach to reviews was used to analyze the existing evidence to answer the review questions. Overall, 28 studies were included. The most common method of data collection was through the use of surveys. Study quality was moderate to strong. Text-based query via an internet search engine was the most commonly identified help-seeking approach. Social media, government or charity websites, live chat, instant messaging, and online communities were also used. Key benefits included anonymity and privacy, immediacy, ease of access, inclusivity, the ability to connect with others and share experiences, and a greater sense of control over the help-seeking journey. Online help-seeking has the potential to meet the needs of those with a preference for self-reliance or act as a gateway to further help-seeking. Barriers to help-seeking included a lack of mental health literacy, concerns about privacy and confidentiality, and uncertainty about the trustworthiness of online resources. Until now, there has been limited development and use of theoretical models to guide research on online help-seeking. Approaches to improving help-seeking by young people should consider the role of the internet and online resources as an adjunct to offline help-seeking. This review identifies opportunities and challenges in this space. It highlights the limited use of theoretical frameworks to help conceptualize online help-seeking. Self-determination theory and the help-seeking model provide promising starting points for the development of online help-seeking theories. This review discusses the use of these theories to conceptualize online help-seeking and identify key motivations and tensions that may arise when young people seek help online.

This book offers a comprehensive scholarly overview of Reddit, one of the most popular and least studied social platforms of the early 21st century. The book inspires new ways of thinking about Reddit, considering it from multiple perspectives: through a historical lens, as a site where identity is forged, as a democracy, as a community, and as a news aggregator and distributor. By bringing theories from computer-mediated communication, communication studies, and sociology to bear on original, large-scale observational analyses of Reddit's communities, this book provides a uniquely comprehensive overview of the platform's first 15 years. Understanding Reddit will help us make sense of how rapidly growing communities function in an era of mass online anonymity. Serving both as a primer on how social behavior on Reddit plays out, and as a way of locating it within multiple theoretical traditions, the book will offer important insights to scholars and students in the disciplines of communication, media studies, information science, internet and emerging media studies, and sociology.

Young Internet users engage in risky or inappropriate behavior online that could either be embarrassing or harmful to their future. As importantly, young Internet users engage in online activities that reveal a great deal about the cost to serve them and their willingness to pay for goods and services, which could be used against them by well-informed sellers. Educational applications that collect users’ information are becoming ubiquitous in the classroom, presenting the opportunity for students’ data to be mined. We are not aware of prior studies that examine parental or students’ attitudes and preferences toward data mining of educational application accounts, and how these attitudes differ across several countries. We used three survey instruments to measure parents’ and students’ attitudes toward data mining of educational applications. Parents in all countries studied prefer far less data mining of students’ online activities than seems to be the current practice. Most importantly, aversion to data mining does not seem to be correlated with awareness of current practices of data mining of teens’ activities. This study highlights regulatory alternatives and suggests future research and future data requirements for designing appropriate regulatory interventions. The nature of the intervention will be guided by the nature of the causes of inappropriate online behavior and inappropriate selection of educational software. Intervention could range from no regulation needed, through providing greater transparency, to new and detailed legal requirements that software providers must meet.

Background Seeking online health information (OHI) has become a common practice globally. The information seekers could face health risks if they are not proficient in OHI literacy. The OHI-seeking behaviors and skills of Chinese college students, the largest proportion of college students in the world, are understudied. This study was aimed to describe OHI-seeking behaviors and skills of college students in Guangdong, China. Methods College students in the Guangdong province with OHI-seeking experience were invited via WeChat, QQ, and Sina Weibo using QR code posters and flyers for participation in this online anonymized questionnaire-based study. Data on demographics, OHI literacy, information resources, search approaches, and behaviors were collected. The relationship between perceived OHI literacy and high-risk behaviors was investigated by bivariate logistic regression analysis. Results Respondents were 1203 college students with a mean age of 20.6 years, females (60.2%), and undergraduates (97.2%). They sought health information via websites (20.3%), WeChat (2.6%), or both (77.1%). Baidu was the main search engine, and baike.baidu.com (80.3%), Zhihu.com (48.4%), and Zhidao.baidu.com (35.8%) were top three among 20 searched websites for information about self-care (80.7%), general health (79.5%), disease prevention (77.7%), self-medication (61.2%), family treatment (40.9%), drugs (37.7%), western medications (26.6%), hospitals (22.7%), physicians (21.4%), and Traditional Chinese Medicine (15.6%). Despite most respondents (78%) lacked confidence in the evidence quality and satisfaction with the results, only 32.4% further consulted doctors. Many (> 50%) would recommend the retrieved information to others. About 20% experienced hacking/Internet fraud. Cronbach’s alpha for the internal consistency of OHI literacy was 0.786. Bivariate logistic regression analysis showed that students who believed they can judge the evidence level of OHI were more likely to self-diagnose (OR = 2.2, 95%CI, 1.6–3.1) and look for drug usage (OR = 3.1, 95%CI, 1.9–5.0). Conclusions This study reveals Chinese college students’ heavy reliance on OHI to manage their own and others’ health without sufficient knowledge/skills to identify misinformation and disinformation. The apparent risky information-seeking behaviors of Chinese college students warrant the provision of regulated, accurate, and actionable health information; assurance of cybersecurity; and health information literacy promotion in colleges by concerned authorities.

In this article a total of fifteen determinants of online shopping behavior have been identified that could have an impact on the strategic management process in e-commerce competitiveness. The main objective of the paper is to evaluate the impact of determinants of online shopping behavior on the strategic management process in e-commerce. The main research methods used in the research are as follows: analysis of secondary data, a questionnaire survey among a selected group of e-commerce companies, a critical analysis and a quality comparison of the actually applied determinants of online shopping behavior. The verification of hypotheses is realized using selected methods of statistical induction and descriptive statistics. In summary, the research has shown there is no relationship between evaluating the quality of determinants companies in e-commerce and evaluating the importance of determinants of online shopping behavior. Determinants have an important impact in the process of creating and realizing an e-commerce strategy, with all e-commerce companies regardless of their size being aware of their practical impact and importance. It can be concluded the importance and quality of determinants of online shopping behavior correspond to the type of strategy and strategic management process in terms of e-commerce competitiveness.

The development of the online environment resulted in the formation of the behavior of all subjects in the online and offline market. This paper responds to current changes that significantly shape the whole society. Therefore, this paper aims to identify changes in online shopping before and during the COVID-19 crisis. The paper is based on primary research in the form of a questionnaire survey among a selected group of respondents that assess the determinants influencing their online shopping decisions before and during the ongoing COVID-19 crisis. The research showed that the COVID-19 crisis was reflected in changes in respondents’ online shopping behavior. Less than a third of respondents declared that they did not change their online shopping behavior during the COVID-19 crisis. The research showed that the frequency of online purchases had increased significantly (more than three times), as well as the percentage volume of goods purchased online. It can also be assessed that the COVID-19 crisis has an impact on future online shopping, and more than 40% of respondents do plan to shop online more after the COVID-19 crisis than during the crisis. However, the relationship between generational cohorts and changes in online shopping behavior before and during the COVID-19 crisis has been demonstrated. Online retailers should be prepared for these changes and should take these changes into account when designing and implementing their e-strategy and thus increase their competitiveness in e-commerce.

Recommendation models for network information that are generally based on user ratings fail to utilize user online behaviours such as reviews and likes, which indicate users’ opinions, attitudes, and emotions. To sufficiently represent user preferences and further enhance recommendation accuracy, a probabilistic linguistic and dual trust network-based user collaborative filtering (PLDTN-UCF) model is proposed in this paper. To reflect the uncertainty of user ratings, an easy-to-use function is proposed to transform the personalized semantics of online reviews into a probability distribution that corresponds to user ratings and construct a probabilistic linguistic rating matrix. Then, the calculation approach of traditional user ratings-based trust network is improved by integrating probabilities to represent the fuzziness of trust. Furthermore, a dual trust network is constructed to represent multi-source interpersonal trust based the on an online behaviours-based trust network and probabilistic linguistic rating matrix-based trust network. Finally, the proposed model is compared to state-of-the-art models using the Douban movie dataset to assess its performance.

To gain insights about dynamic networks, the dominant paradigm is to study discrete snapshots, or timeslices, as the interactions evolve. Here, we develop and test a new mathematical framework where network evolution is handled over continuous time, giving an elegant dynamical systems representation for the important concept of node centrality. The resulting system allows us to track the relative influence of each individual. This new setting is natural in many digital applications, offering both conceptual and computational advantages. The novel differential equations approach is convenient for modelling and analysis of network evolution and gives rise to an interesting application of the matrix logarithm function. From a computational perspective, it avoids the awkward up-front compromises between accuracy, efficiency and redundancy required in the prevalent discrete-time setting. Instead, we can rely on state-of-the-art ODE software, where discretization takes place adaptively in response to the prevailing system dynamics. The new centrality system generalizes the widely used Katz measure, and allows us to identify and track, at any resolution, the most influential nodes in terms of broadcasting and receiving information through time-dependent links. In addition to the classical static network notion of attenuation across edges, the new ODE also allows for attenuation over time, as information becomes stale. This allows 'running measures' to be computed, so that networks can be monitored in real time over arbitrarily long intervals. With regard to computational efficiency, we explain why it is cheaper to track good receivers of information than good broadcasters. An important consequence is that the overall broadcast activity in the network can also be monitored efficiently. We use two synthetic examples to validate the relevance of the new measures. We then illustrate the ideas on a large-scale voice call network, where key features are discovered that are not evident from snapshots or aggregates.

Trust plays an important role in social media communication. For companies, trust is an important determinant of successful online communication. Thus, there is a pressing need to understand consumers’ trust in the socially mediated environment This paper presents a research study focused on modelling trust dimensions on social media. The main objective of this research is to identify which dimensions of trust play the most significant role in building trust in communication on social media. The second objective is focused on the development and validation of the five-factor trust measurement scale. A questionnaire survey (n=1000) was used as a tool to gather data. Exploratory factor analysis, confirmatory factor analysis and multiple regression analysis were used for data analysis and modelling. The research findings provide a deeper understanding of the factors that influence trust in the context of social media communication and expand existing knowledge. The conducted research uncovers the main trust dimensions that can be used to influence consumers’ attitudes toward companies operating online. Our model can help companies shape their communication to the right tone by highlighting the crucial factors that have a direct influence on trust.

Online discussion communities have become a widely used medium for interaction, enabling conversations across a broad range of topics and contexts. Their success, however, depends on participants' willingness to invest their time and attention in the absence of formal role and control structures. Some studies of online communities argue that individuals are driven by self-interest, while others emphasize more altruistic motivations. To get beyond these inconsistent explanations, the authors offer a model that brings dissimilar rationales into a single conceptual framework and shows the validity of each rationale in explaining different online behaviors. Drawing on typologies of organizational commitment, they argue that members may have psychological bonds to a particular online community based on need, affect, and/or obligation. They develop hypotheses that explain how each form of commitment to a community affects the likelihood that a member will engage in particular behaviors. Results indicate that each form of community commitment has a unique impact on each behavior.