User Behavior Research Research Articles

Are Active Users the Most Central to Hacker Social Networks? A Comparative Analysis of Public and Private Online Network Structures Among Hackers

ABSTRACT The last decade witnessed significant research of user behavior and social networks within online hacker forums and illicit markets. Researchers have used the quantifiable nature of forum posting behaviors to assess network ties between actors and identify key participants based on their connections. These studies are based on the publicly identifiable associations between actors in public posts. Participants within forums can also connect with users through private messaging systems linking users directly through a sort of e-mail-based exchange. Few have considered how the public and private message networks of actors differ and what can be gleaned from their analysis. This study employed a quantitative analysis of a highly popular web forum used by hackers involved in both legal and criminal hacks. First, the networks were built of the relationships between 1,313 users across 12,531 threads and 19,862 public posts, and between those users’ 1,738 private messages. Then the centrality on hidden networks was estimated from the centrality on the visible networks. The implications of this study for policy and our understanding of online network structures are discussed.

Investors’ willingness to use robo-advisors: Extrapolating influencing factors based on the fiduciary duty of investment advisors

Robo-advisors are increasingly seen as a solution for the growing demand for timely and actionable financial advice. However, systematic barriers to their deployment and use persist. Understanding the factors that influence investors' willingness to consult with robo-advisors is key to their wide-scale adoption. This research aims to isolate the factors influencing the willingness to adopt robo-advisors by investment advisory services. We focus on three adoption drivers: (1) performance of robo-advisors, (2) human-computer interaction, and (3) the reputation of software suppliers. Results indicate that ‘performance efficacy’, ‘perceived ease of use’, ‘customer education’, and ‘corporate reputation’ positively influence the perceived value, leading to higher adoption intention. Additionally, ‘performance efficacy’, ‘perceived privacy protection’ and ‘corporate reputation’ positively contributes to the building of trust, which in turn leads to higher adoption intention and asset allocation ratio. We found that low-experience investors were “value-driven”, while highly experienced investors were “trust-driven” when it came to adoption intent. The research highlights the potential of artificial intelligence-based applications for user behavior research and suggests design considerations for robo-advisor developers to influence positive adoption in financial advisory services.

Drivers of Crowdfunding Adoption: A Research of User Behavior in Indonesia

Drivers of Crowdfunding Adoption: A Research of User Behavior in Indonesia

Is mouse dynamics information credible for user behavior research? An empirical investigation

Mouse dynamics, information on user’s interaction with a computer mouse, are in vogue in machine learning for purposes such as recommendations, personalization, prediction of user characteristics and behavioral biometrics. We point out a blind spot in current works involving mouse dynamics that originates in underestimating the gravity of the characteristics of the mouse device and configuration on the data that mouse dynamics are inferred from. In a controlled study with N=32 participants, across three kinds of mouse interaction activities, we collect data for mouse dynamics utilizing a variety of mouse parameter configurations. We show that mouse dynamics commonly used in studies can be significantly altered by differences in mouse parameters. Out of 108 evaluated mouse dynamics metrics, 95 and 84 are affected between two conducted studies. A machine learning model’s performance can be warped by the mouse parameters being used. We demonstrate on a prediction task that mouse parameters cannot be approached uniformly and without consideration. We discuss methodological implications — how mouse dynamics studies should account for the diversity of mouse-related conditions.

The Cases of Burner Accounts on Weibo: Do Burner Accounts Really Hide Your True Identity?

A burner account refers to “an often-temporary social media account that is created for the purpose of remaining anonymous”. On the one hand, Burner account users hide their private information, and on the other hand, they carry out bold self-disclosure in many aspects such as emotions and interests. Such user behavior research may be of great significance for us to understand the emotions and interests suppressed by acquaintances in the relationship society. Burner accounts are likely to continue to be a typical aspect of online communication for the foreseeable future as social media sites continue to struggle with the trade-offs between transparency and privacy. Meanwhile, the use of burner accounts also highlights the potential risks in the context of government supervision.

Social media user behavior analysis applied to the fashion and apparel industry in the big data era

With the rapid development of the Internet and new media, the enormous data from social media and other public platforms have attracted increasing attention to user behavior research. Fashion is a hot topic for both the general public and the social economy, so there is great potential for exploring and manipulating social media data for the development of the fashion industry in the current era. This paper aims to explore the current status of social media user behavior analysis applied to the fashion and apparel industry for advanced product development, branding strategy planning and the resolution of other decision-making problems in the big data context. First, articles were retrieved from the database "Web of Science". With the assistance of experts, 201 articles were determined for further study. Next, the evolution of hot topics within the domain was visualized and discussed through bibliometric analysis. Then, the application of social media data in the fashion domain was investigated, and common data mining methods were discussed. Finally, the paper summarized the development status of social media user behavior analysis (SMUBA) applied to the fashion and apparel industry and put forward the future prospect under the framework of mass customization in the big data era.

What determines the battery recycling behavior of electric bike users?: Introducing recycling convenience into the theory of planned behavior

To protect the environment, China attaches great importance to waste lead-acid battery recycling of electric bikes (e-bikes). If China wants to do a good job in recycling, it cannot do without the strong support of e-bike users. The research introduces recycling convenience into the theory of planned behavior (TPB) to verify the impact of recycling convenience on user behavior. The structural equation model (SEM) was used to investigate the recycling behavior of 429 e-bike users in Tangshan, China. The results show that attitude, subjective norms, and recycling convenience all can affect e-bike users' behavior intention positively and significantly, while perceived behavior control can not affect intention significantly. Simultaneously, this study established the beneficial and significant effects that perceived behavior control and behavior intention can have on e-bike users' recycling behavior. In addition, the study also verified that recycling convenience can indirectly affect users' recycling intention by influencing users’ attitude and subjective norms, indicating that this extended theoretical framework of planned behavior is appropriate for e-bike user behavior research.

Empirical investigation of the impact of overload on the discontinuous usage intentions of short video users: a stressor-strain-outcome perspective

PurposeThis study focuses on perceived overload from environmental stimuli and individual psychology and behavioral interactions. It constructs a theoretical model with overload as the key stressor based on the stressor-strain-outcome (SSO) model. The authors argue that system feature overload (SFO), information overload, and social overload lead to two psychological strains: fear of missing out (FoMO) and fatigue among users of short video platforms, affecting their discontinuous usage intentions.Design/methodology/approachTo test the hypotheses, the authors conducted a questionnaire survey on 412 users' short video platform usage and empirically tested the constructed model using the research tool SmartPLS 3.3.2.FindingsThe results of data analysis showed that most of the hypotheses were supported. Specifically, system feature overload, information overload and social overload all positively affected FoMO. However, SFO and information overload significantly affected fatigue. There was no significant relationship between social overload and fatigue. In addition, both FoMO and fatigue negatively influenced users' discontinuous usage intentions.Originality/valueThe current research on user behavior in information systems tends to focus on the influence in the positive direction and less on the negative direction. The research on discontinuous usage intention (DUI) is a very new research topic. This research studies the influencing factors of users' discontinuous behavior from the perspective of perceptual overload. It provides a unique view for future short video platform user behavior research, with significant theoretical contributions and essential practice for short video platform operators to improve services.

Designing Guided User Tasks in VR Embodied Experiences

Virtual reality (VR) offers extraordinary opportunities in user behavior research to study and observe how people interact in immersive 3D environments. A major challenge of designing these 3D experiences and user tasks, however, lies in bridging the inter-relational gaps of perception between the designer, the user, and the 3D scene. Paul Dourish identified three gaps of perception: ontology between the scene representation and the user and designer interpretation, intersubjectivity of task communication between designer and user, and intentionality between the user's intentions and designer's interpretations. We present the GUsT-3D framework for designing Guided User Tasks in embodied VR experiences, i.e., tasks that require the user to carry out a series of interactions guided by the constraints of the 3D scene. GUsT-3D is implemented as a set of tools that support a 4-step workflow to (1) annotate entities in the scene with navigation and interaction possibilities, (2) define user tasks with interactive and timing constraints, (3) manage interactions, task validation, and user logging in real-time, and (4) conduct post-scenario analysis through spatio-temporal queries using ontology definitions. To illustrate the diverse possibilities enabled by our framework, we present two case studies with an indoor scene and an outdoor scene, and conducted a formative evaluation involving six expert interviews to assess the framework and the implemented workflow. Analysis of the responses show that the GUsT-3D framework fits well into a designer's creative process, providing a necessary workflow to create, manage, and understand VR embodied experiences.

Challenges and opportunities of blockchain energy applications: Interrelatedness among technological, economic, social, environmental, and institutional dimensions

The energy sector is undergoing a transition of decarbonization, decentralization, and digitalization. This paper explores the application of blockchain in this transition. Through qualitative content analysis, expert interviews and discussion rooted in recent literature, key insights on the practical challenges and opportunities of blockchain energy applications are investigated. This is done in technological, economic, social, environmental, and institutional dimensions in order to propose holistic insights. Key dentified issues include scalability, data privacy, costs of change, market dynamics, user experience, skills, multi-stakeholder governance, and regulatory change. Key identified opportunities also range across these dimensions, such as blockchain advancements, power market development, user research, and regulatory sandboxes. While most research on blockchain energy applications has been from the technological lens, this paper contributes with a multi-dimensional approach. The interrelatedness among these dimensions is one of the key messages of this paper. Both corporate strategy and public policy development need to integrate user behavior research, business model innovation and regulatory experimentation for a holistic approach in understanding and implementing blockchain, and other emerging technologies. It is suggested that the multi-dimensional challenges and opportunities identified in this study, and functioning of their interrelatedness, are of interest for further exploration both in academia and among practitioners.

E-word of mouth sentiment analysis for user behavior studies

Nowadays, online word-of-mouth has an increasing impact on people's views and decisions, which has attracted many people's attention.The classification and sentiment analyse in online consumer reviews have attracted significant research concerns. In this thesis, we propose and implement a new method to study the extraction and classification of online dating services(ODS)’s comments. Different from traditional emotional analysis which mainly focuses on product attribution, we attempted to infer and extract the emotion concept of each emotional reviews by introducing social cognitive theory. In this study, we selected 4,300 comments with extremely negative/positive emotions published on dating websites as a sample, and used three machine learning algorithms to analyze emotions. When testing and comparing the efficiency of user's behavior research, we use various sentiment analysis, machine learning techniques and dictionary-based sentiment analysis. We found that the combination of machine learning and lexicon-based method can achieve higher accuracy than any type of sentiment analysis. This research will provide a new perspective for the task of user behavior.

Research on the mechanism of knowledge diffusion in the MOOC learning forum using ERGMs

Research on the mechanism of knowledge diffusion in the MOOC learning forum using ERGMs

The role of transaction cost and trust in e-loyalty: a mixed-methods study of ride-sharing

PurposeThe purpose of this paper is to explore the trust antecedents and the effect of trust and transaction cost on passengers' e-loyalty in the context of mobile commerce enabled ride-sharing.Design/methodology/approachA mixed-methods research is adopted to investigate the phenomena of interest. The qualitative study was used to identify the context-specific trust antecedents. The quantitative study investigated the effects of trust and transaction cost on e-loyalty by combining the results of qualitative study.FindingsThree important context-specific trust antecedents were identified in qualitative study, namely online rating score, service quality and driving skills. The quantitative study indicates that driving skills, explicit cost and implicit cost are positively associated with trust. Trust and implicit cost have direct and positive effects on e-loyalty.Research limitations/implicationsThis study contributes to understanding passengers' trust towards drivers in the context of mobile commerce enabled ride-sharing and the effect of trust on e-loyalty by including the transaction cost.Practical implicationsManagement to enhance passengers' e-loyalty to ride-sharing might involve the measures to promote trust relationship.Originality/valueLimited research has explored trust relationship for enhancing e-loyalty in the context of ride-sharing. The current study provides a novel contribution through an exploration of trust antecedents and the effects of transaction cost and trust on e-loyalty. The study has thrown light on the use of mixed-methods design in the research of user behavior in sharing economy.

Application of User Behavior Research Method in the Vehicle Navigation Interface Design

The relationship between user behavior research methods and vehicle navigation interface design has been the focus of much recent research. This paper aims to improve the vehicle navigation interface use experience through user behavior and emotional, and allow user to better accept the navigation information in the vehicle. Emotional behavior analysis and multimodal interaction information integration are the key approaches which includes causal loop diagrams and information diagrams used to build the reference model of vehicle navigation interface design. The result of the measurement indicates that user behavior research can enable information interaction projects to build upon and transcend designers’ expertise and expectations during vehicle navigation interface design. The research, therefore, will highlight not only the importance of users behavior and experience in interface design, but also the necessity of taking effective measures to cater to users’ emotional needs.

User Behavior Research of Information Security Technology Based on TAM

By analyzing the present applying situation and influential factors of the information security technology, considering technological utility, cognitive cost, social impact, individual innovation, computer self-efficacy and other external variables, this paper constructs a model of user behavior of information security technology based on TAM. Through questionnaire to collect data and SPSS to perform reliability analysis, validity analysis, correlation analysis and regression analysis, the model in this paper is verified to be effective. Finally, some relative recommendations for the development of Chinese information security technology are put forward.

Consuming information systems: An economic model of user satisfaction

This paper has two major objectives. The first objective intends to answer the following question which is of significant interest to information system (IS) researchers and practitioners: How does user satisfaction (satisfaction) respond to changes in system use and system attributes? The second and more ambitious objective is to promote the application of economic theories in user behavior research. In contrast to prior research that conceived the development of user satisfaction as an information valuation and integration process, we consider such development to be embedded in the IS consumption process, that is, users gain utility (satisfaction) from consuming (using) the system. This perspective enables us to re-conceptualize user satisfaction as a proxy of utility and apply utility research in economics to study user satisfaction. An economic model of user satisfaction was developed. Two empirical studies were conducted to examine the research model. The findings confirmed the consumptive nature of user satisfaction. Apart from enriching our understanding of user satisfaction, this research demonstrates the usefulness of economic theories in user behavior research.

An evaluation tool for research of user behavior in a realistic mobile environment

User behavior is significantly influenced by the surrounding environment. Especially complex and dynamically changing environments (like mobile environment) are represented by a wide variety of extraneous variables, which influence the user behavior in an unpredictable and mostly uncontrolled way. For researchers, it is challenging to measure and analyze the user behavior in such environments. We introduce a complex tool—the IVE tool—which provides a unique way of context visualization and synchronization of measured data of various kinds. Thanks to this tool it is possible to efficiently evaluate data acquired during complex usability tests in a mobile environment. The functionality of this tool is demonstrated on the use case “Navigation of visually impaired users in the building with support of a navigation system called NaviTerier.” During the experiment, we focused on collection and analysis of data that may show user stress and which may influence his/her ability to navigate. We analyzed objective data like Galvanic Skin Response parameter (GSR), Heart Rate Variability parameters (HRV) and audio video recordings and also subjective data like the user’s subjective stress feeling and observation of the user’s behavior.