Online Behavior Research Articles

Mental Health and (Online) Behaviors during the COVID-19 Pandemic in Spain: A Network-Based Approach.

The COVID-19 pandemic has contributed to the increase in mortality and morbidity rates globally, but it has also led to a generalized worsening of mental health and risk behaviors in different population groups regardless of the measures adopted by different governments. In this paper, using data from a Spanish survey of emotional well-being, we aim to explore through mixed graphical models the complex structure of relationships between the mental health of populations, their lifestyles, and forms of cultural and leisure consumption during the pandemic. The results bring to light some interesting findings, such as the association between teleworking and greater rest or greater stress with the use of social media, a variable that enables the connection with other mental health problems of greater severity. Increased physical activity and the consumption of streaming content at home, as well as increased care for family, friends, and neighbors, are some of the variables that show relevant associations. These findings highlight the usefulness and versatility of this network approach for the study of health behaviors and health outcomes, which offer the researcher a holistic and organic view of the relational structure of complex data characterized by high dimensionality and variables with different levels of measurement.

Online shopping behaviour on social media platforms from the perspective of trust and flow experience: a SEM-Neural Network Modeling

This study aims to examine online shopping behaviour on social media platforms. This study formulates a research model integrating trust with the flow theory and some basic constructs of the UTAUT. To analyze the data from an online survey involving 305 participants actively making online purchases through social media platforms. This study applied the Structural Equation Modeling-Artificial Neural Networks (SEM-ANN) technique. Incorporating statistically significant SEM findings, the ANN model was used to analyze linear and nonlinear interactions among proposed variables. The research findings demonstrate that flow emerges as the most significant determinant, succeeded by effort expectancy, social influence, and performance expectancy, in defining the concept of trust. However, the sensitivity analysis using ANN indicates that effort expectancy is the most important factor in establishing trust, followed by flow, social influence, and performance expectancy. The predictive power of intention to use is noteworthy in determining actual use behaviour, with trust and flow emerging as influential factors favourably impacting this intention.

Post Truth: Ethics and Digital Security

In an increasingly advanced digital era, the phenomenon of "post-truth" has become a major concern in the study of digital ethics and security. This article explores the impact of the emergence of post-truth on morality and security in the digital realm. The research method used is literature analysis to investigate how post-truth affects online behavior, alters the dynamics of information, and increases vulnerability to cyberattacks. Additionally, this article introduces several ethical strategies and principles that can be applied to address these challenges, including enhancing digital literacy, implementing stricter regulations, and promoting better understanding of the consequences of spreading false information. Thus, this article illustrates the importance of integrating ethics and digital security as crucial steps towards a more responsible and secure digital ecosystem.

Exploring the Mechanism of Adult Users' Cyber-Aggression Against Adolescents: The Roles of Online Communication, Age Group Identity, and Online Moral Disengagement.

The increasing prevalence of adults' prejudice against adolescents on the Internet could cause opposing attitudes and even online aggression against teenagers. Yet, such age discrimination is less challenged compared to other social biases in cyberspace. Employing a social identity approach, this study aims to explore how features of online communication, teen-related personal experiences, and the dual identity of adult aggressors influence online moral disengagement (OMD), motives, and behaviors for cyber-aggression. We conducted an online survey of 767 Chinese adults in May 2023. The results demonstrated that perceived controllability of online speech, negative teen-related online experiences, and generation-based bias were positively associated with OMD. Next, adult respondents' self-serving motives positively predicted moderate and severe cyber-aggression, while educational motives only increased moderate cyber-aggression. Mediation analysis revealed that generation-based bias was the sole significant factor that amplified OMD, self-serving motives, educational motives, and cyber-aggression behaviors. In contrast, the effects of lifestage-based bias were insignificant. Our findings yield insights into individuals' moral transgressions in digital environments and shed light on the dynamics of the identity of adult aggressors in age-based discrimination. This study suggests that empathy from adults and age-appropriate prevention by online platforms are crucial to address online aggression against young generations.

Research on the motivation for viewer addiction to live streaming: a cross-cultural investigation of China and the USA

PurposeWith the increasing popularity of live streaming, the exploration of online behaviors on live streaming platforms has become a research hot spot in academia. However, the literature lacks cross-cultural investigations into live streaming addictive (LSA) behaviors among viewers. To address this gap, based on stimulus-organism-response (SOR) theory and motivation theory, this study investigates how information seeking, sensation seeking and community commitment (stimulus) affect hedonic and utilitarian motivation (organism), which in turn influence viewers’ LSA behaviors (response). This study also compares American and Chinese viewers to understand how LSA behaviors differ across national cultures.Design/methodology/approachWe surveyed live stream viewers in both nations, collecting 758 valid samples including 377 Chinese respondents and 381 American respondents for use with the research model. A partial least squares (PLS) approach is employed for data analysis.FindingsThe results show that information seeking increases utilitarian motivation, sensation seeking increases hedonic motivation, and community commitment strengthens both hedonic and utilitarian motivation. Both hedonic motivation and utilitarian motivation positively affect LSA behaviors. In addition, based on cross-cultural analysis, we found that there was a significant mediating path common to the respondents in China and the USA (i.e. sensation seeking ? Hedonic motivation ? LSA).Originality/valueThe findings of this study make theoretical contributions to live streaming research and offer practical guidance for live streaming firms to formulate proper marketing strategies. Last, this study outlines several limitations and possible directions for future research.

Research on the Relationship between Ideological and Political Education in Universities and College Students’ Online Behaviors

Research on the Relationship between Ideological and Political Education in Universities and College Students’ Online Behaviors

Consumer Behavior in Online Shopping: A Comparative Analysis of Generational Differences

The consumer behavior in online shopping across different generations, focusing on Millennials, Generation X, and Baby Boomers. With the proliferation of e-commerce platforms, understanding how generational cohorts engage with online shopping is crucial for businesses aiming to effectively target and cater to diverse consumer preferences. Utilizing a quantitative research approach, this comparative analysis explores factors influencing online purchase decisions, including trust in online retailers, perceived risks, shopping motivations, and preferences for digital payment methods. variations in consumer behavior among generational cohorts. Millennials, characterized by their digital proficiency and preference for convenience, exhibit a higher propensity for online shopping and are more likely to embrace emerging technologies such as mobile commerce and social media influencers. In contrast, Generation X consumers prioritize product reviews and brand reputation when making online purchases, emphasizing trust and reliability in e-commerce transactions. Baby Boomers, while increasingly adopting online shopping for convenience, express concerns about data security and prefer traditional payment methods.

Internet behavioral models for improving internet quality of service or user profiling: a systematic literature review

Internet behavior models have found applications across diverse domains, notably in internet addiction, customer satisfaction analysis, user purchasing behavior prediction, and optimizing internet of things (IoT) sensor performance. However, a notable gap exists in exploring these models in enhancing internet quality of service (QoS), specifically in campus settings, intricately linked to the nuances of students' online behavior. This study elucidates the strategic utilization of internet behavioral models for augmenting internet QoS and facilitating user behavior analysis. Creating datasets grounded in internet users' access behavior represents a pivotal phase, with explicit, implicit, and mixed methods emerging as the prevailing approaches. In this comprehensive literature review, we systematically scrutinized the methods, techniques, and inherent characteristics of constructing internet behavior models according to a systematic literature review process. The qualitative findings extracted from the systematic review encapsulated 1,046 articles, meticulously classified according to predefined inclusion and exclusion criteria. Subsequently, 35 articles were judiciously selected for in-depth analysis. This study culminated in identifying the most pertinent methodologies and salient features pivotal to construct robust internet behavior model for improving internet QoS and user experience.

Self-interest or ethic: Consumer segmentation for purchasing agricultural products online based on attitude in China

This paper aims to segment online consumers based on their attitude toward self-interest and ethical attitudes and explore the impact of these attitudes on the purchasing behavior of agricultural products online in China. The study was conducted using 633 online survey responses from consumers who have purchased agricultural products online in China. First, to validate the relationship between attitude and behavior by structural equation modeling. Next, the number of segments was determined using K-means. Finally, Pearson Chi-square difference tests were performed to analyze demographic and behavioral variables and identify each segment’s characteristics. The results of this study provide a segmentation analysis of the online market for agricultural products in China. The four segments identified are pure ethical consumers, information communicators, brand-quality pursuers, and well-heeled shoppers. Additionally, this study reveals the characteristics of each segment based on demographic and behavioral variables. This study provides a novel approach to segmenting Chinese consumers who purchase agricultural products online based on their attitudes toward self-interest and ethical attitudes, aiming to understand the impact of these attitudes on their purchasing behavior. Moreover, from an ethical consumerism perspective, it explores the effect of ethical information on purchasing agricultural products online, highlighting its significant implications for online marketing strategies.

Online Signals of Extremist Mobilization.

Psychological theories of mobilization tend to focus on explaining people's motivations for action, rather than mobilization ("activation") processes. To investigate the online behaviors associated with mobilization, we compared the online communications data of 26 people who subsequently mobilized to right-wing extremist action and 48 people who held similar extremist views but did not mobilize (N = 119,473 social media posts). In a three-part analysis, involving content analysis (Part 1), topic modeling (Part 2), and machine learning (Part 3), we showed that communicating ideological or hateful content was not related to mobilization, but rather mobilization was positively related to talking about violent action, operational planning, and logistics. Our findings imply that to explain mobilization to extremist action, rather than the motivations for action, theories of collective action should extend beyond how individuals express grievances and anger, to how they equip themselves with the "know-how" and capability to act.

Trends in Contraceptive Use and Influencing Factors Among Korean Adolescent Girls With Sexual Intercourse Experience (2013 to 2022)

Purpose: This study aimed to identify trends in contraceptive use and methods, as well as the influencing factors among Korean adolescent girls with sexual intercourse experience.Methods: Secondary data analysis was performed using data from the 2013−2022 Youth Health Behavior Online Survey. Participants were 9,562 adolescent girls who had experienced sexual intercourse in middle and high schools in Korea. Descriptive statistics, the chi-square test, the Cochran-Armitage trend test, and logistic regression were used for data analysis.Results: The reported prevalence of consistent contraceptive use during sexual intercourse significantly increased from 27.0% in 2013 to 46.1% in 2022 (p<0.01). The rate of modern contraceptive use increased from 79.4% in 2013 to 84.8% in 2022 (p for trend <0.01). Factors influencing contraceptive use included age, school type by sex, academic performance, economic status, residential type, lifetime smoking, and sexual education. Factors influencing modern contraceptive use included school type by sex, economic status, residential type, and lifetime smoking.Conclusion: The results of this study indicate that more than half of the adolescent girls with sexual experience do not consistently use contraception, and some of them use unreliable contraceptive methods. Efforts are needed to improve modern contraceptive use among adolescent girls.

Mental Health in Adolescents with Allergic Disease : Using Data from the 2021 Korean Youth’s Health Behavior Online Survey

Mental Health in Adolescents with Allergic Disease : Using Data from the 2021 Korean Youth’s Health Behavior Online Survey

Accessing child sexual abuse material: Pathways to offending and online behaviour

Accessing child sexual abuse material: Pathways to offending and online behaviour

Unravelling the dynamics of child sexual exploitation material circulation on the Dark Web.

In recent years, there has been a significant increase in the detection of child sexual exploitation material (CSEM), with perpetrators increasingly turning to advanced encryption technologies to conceal their activities. This study delves into data from a Brazilian Federal Police operation on the Tor network, aimed at disrupting these illicit activities. We uncovered patterns indicating strong user preferences for certain content categories, suggesting the existence of distinct groups with shared interests. Additionally, our findings reveal consistent activity patterns among users, including specific 24-hour, 12-hour, and 6-hour consumption cycles. This research offers insights into the online behavior related to CSEM, providing a foundation for further investigation and the development of effective policy measures.

Anomaly prediction of Internet behavior based on generative adversarial networks.

With the popularity of Internet applications, a large amount of Internet behavior log data is generated. Abnormal behaviors of corporate employees may lead to internet security issues and data leakage incidents. To ensure the safety of information systems, it is important to research on anomaly prediction of Internet behaviors. Due to the high cost of labeling big data manually, an unsupervised generative model-Anomaly Prediction of Internet behavior based on Generative Adversarial Networks (APIBGAN), which works only with a small amount of labeled data, is proposed to predict anomalies of Internet behaviors. After the input Internet behavior data is preprocessed by the proposed method, the data-generating generative adversarial network (DGGAN) in APIBGAN learns the distribution of real Internet behavior data by leveraging neural networks' powerful feature extraction from the data to generate Internet behavior data with random noise. The APIBGAN utilizes these labeled generated data as a benchmark to complete the distance-based anomaly prediction. Three categories of Internet behavior sampling data from corporate employees are employed to train APIBGAN: (1) Online behavior data of an individual in a department. (2) Online behavior data of multiple employees in the same department. (3) Online behavior data of multiple employees in different departments. The prediction scores of the three categories of Internet behavior data are 87.23%, 85.13%, and 83.47%, respectively, and are above the highest score of 81.35% which is obtained by the comparison method based on Isolation Forests in the CCF Big Data & Computing Intelligence Contest (CCF-BDCI). The experimental results validate that APIBGAN predicts the outlier of Internet behaviors effectively through the GAN, which is composed of a simple three-layer fully connected neural networks (FNNs). We can use APIBGAN not only for anomaly prediction of Internet behaviors but also for anomaly prediction in many other applications, which have big data infeasible to label manually. Above all, APIBGAN has broad application prospects for anomaly prediction, and our work also provides valuable input for anomaly prediction-based GAN.

Review of Policies and Practices to Prevent Technology-Facilitated Child Sexual Abuse Within Youth-Serving Organizations in the United States

ABSTRACT Technology-facilitated child sexual abuse (TF-CSA), or child sexual abuse that occurs online or through electronic communication, is a preventable public health problem that can be addressed within youth-serving organizations (YSOs). This study is a review of a purposive sample of organizational policies and practices designed to prevent TF-CSA collected from 13 national and local YSOs in the United States. Documents were coded to identify practices to prevent TF-CSA related to YSO activities or YSO staff, volunteers, or participants. Qualitative analysis indicated that YSOs included seven common practices to prevent TF-CSA in their documents. These practices included transparent electronic communication between youth and YSO staff; codes of conduct and online behavior agreements related to youth; monitoring the YSO’s online presence; parental controls for youth online activity; safety behaviors for online activity for staff, parents, and youth; parent and youth trainings for youth online engagement and prevention of TF-CSA; and practices to address staff policy violations. Most prevention practices documented by YSOs identified in this study are consistent with emerging literature on TF-CSA prevention. Key gaps include protections for youth from groups inequitably burdened by TF-CSA and evaluation of the implementation and effectiveness of practices in preventing TF-CSA across settings and populations.

Trial of Memory: Legal Regulation as a Tool of Memory Politics in Contemporary Russia

The article examines how law enforcement sanctions, typically applied to real-life actions, are being transferred to online activities. Building on François Hartog’s ideas, the study links memorial legislation to a new “regime of historicity,” highlighting its unique role in commemoration. By examining relevant laws and media discussions, the study follows the evolution of memorial legislation, demonstrating its importance in commemorating the Great Patriotic War in post-Soviet symbolic politics. Analysis of the amendments to Article 354.1 of Russia’s Criminal Code from its original formulation in 2014 to the revisions in 2021 reveals the shifting legal landscape surrounding online commemorative practices. As virtual spaces are gaining prominence in public discourse and legal interpretations, the boundaries between online activities and real-world actions are becoming increasingly blurred. The key trends in this process include the growing reliance on virtual platforms for information dissemination, the evolving notion of publicity in legal contexts pertaining to online behavior, and the broadening enforcement of Article 354.1. This research sheds light on the intricate interplay between memory politics, virtual spaces, and legal frameworks, reflecting broader societal shifts in information consumption and expression.

Maladaptive daydreaming and problematic online behaviors: A network analysis approach

Previous evidence showed that Maladaptive Daydreaming (MD) is positively associated with different Problematic Online Behaviors (POBs). This study aimed to investigate the mutual relationship between MD and several POBs. Data were collected from 1209 participants, aged 18–73 (M = 30.59, SD = 12.26), through self-report questionnaires assessing MD and POBs, including problematic online gambling, problematic online gaming, problematic cybersex, Problematic Social Media Use (PSMU), problematic online shopping, and cyberchondria. Two psychometric network analyses were performed to examine the associations between all POBs at item levels, and between MD and POBs at construct levels. Results revealed six distinct communities, supporting the specificity of each POB. Furthermore, MD was found to be more strongly associated with PSMU and cyberchondria, and weakly associated with problematic online gaming, problematic cybersex, and problematic online shopping. The mutual relationships between MD and POBs might have relevant implications for the assessment and treatment of these clinical conditions.

Integral Emotions and Incidental Emotions of Consumers in Impulse Buying Behavior Online

Integral Emotions and Incidental Emotions of Consumers in Impulse Buying Behavior Online

The Instagram Paradox: Examining Its Role in Shaping Mental Health Among Young Adults--A Comprehensive Analysis

Instagram has become a ubiquitous part of young adults' lives, profoundly shaping their mental health and well-being. This research was conducted to investigate the pervasive influence of Instagram usage among young adults aged 17-22, particularly focusing on its impact on anxiety, depression, and self-esteem. The rationale for this study stems from the growing concern about the psychological effects of prolonged exposure to idealized images and lifestyles presented on social media. Utilizing a comprehensive survey methodology, data was collected from a diverse sample of young adults. The results reveal that 95.2% of participants use Instagram daily, with nearly half spending over four hours on the platform each day. The study highlights significant mental health repercussions, with 70% of respondents reporting feelings of anxiety, depression, and inadequacy attributed to their Instagram use. These findings underscore the critical need for interventions to mitigate the negative impact of Instagram on mental health and to promote healthier online behaviors and interactions. The implications of this research are far-reaching, suggesting that both individual users and social media platforms must take proactive steps to foster digital environments that support mental well-being and reduce the psychological burden on young adults.