Your click decides your fate: Inferring Information Processing and Attrition Behavior from MOOC Video Clickstream Interactions

In this work, we explore video lecture interaction in Massive Open Online Courses (MOOCs), which is central to student learning experience on these educational platforms. As a research contribution, we operationalize video lecture clickstreams of students into cognitively plausible higher level behaviors, and construct a quantitative information processing index, which can aid instructors to better understand MOOC hurdles and reason about unsatisfactory learning outcomes. Our results illustrate how such a metric inspired by cognitive psychology can help answer critical questions regarding students' engagement, their future click interactions and participation trajectories that lead to in-video & course dropouts. Implications for research and practice are discusse

A Hybrid SEM-fsQCA Approach to Examine Spectators’ Toxic Behavior in Professional Team Esports

The rising popularity of professional team esports has brought along an unwelcome increase in toxic behavior (TB) during live esports streams. To better understand the dynamics of TB, we collected a survey sample of League of Legends (LoL) Esports audience (n = 430) members and delved into the influence of Big Five and Dark Triad personality traits, game identification, team identification, as well as demographics on TB. Employing the fuzzy set qualitative comparative analysis (fsQCA) and partial least squares structural equation modeling (PLS-SEM), we found that conscientiousness, openness to experience, neuroticism, psychopathy, game identification, and gender were significant predictors of TB. The fsQCA results highlighted that both high or low levels of TB would arise from a composite mix of variables rather than a single determinant. This study emphasizes the intricate interconnections between various TB influencers and provides new insights into the complexity of TB

Assessing the Effects of Communication Media Affordances and the Awareness of Media Security on Knowledge Sharing Behavior

Global Software Development (GSD) team members engage in intellectual activities that involve sharing business domain knowledge and technical knowledge across geographical areas, which is crucial to the successful development of software. In global software development, media choice may influence how virtual teams create and share knowledge. As digital technology advances and organizations become more digitally transformed, current communication theories for media selection lack the explanation to the complicated phenomena with the use of advanced media technologies. There have been many studies focused on the effectiveness of media, but they did not include user’s understanding of system security and its influence on knowledge sharing behavior. However, affordance theory explains the utility with both social actors and technical features. The use of media may be shaped by features of technologies and user’s perception on system security. The goal of this study was to empirically assess the effects of media affordances and media security awareness on knowledge sharing behaviors among GSD team members with the lens of affordance theory. In this study, data was collected through survey from 214 GSD employees, after inviting 1000 employees to participate. The survey data was analyzed to test the effects of communication media affordance and user’s awareness of media security on behavior in knowledge sharing. The analysis results show that awareness of media security had significant moderating effects on the relationships from some actualized media affordances to implicit knowledge sharing. The results of this study revealed positive relationships between perceived media affordances and actualized media affordances. The results also showed that organization tenure had a significant effect on implicit knowledge sharing, and professional tenure had a significant effect on explicit and implicit knowledge behavior. This study contributed to the body of knowledge in organizational communication literature by providing new insights into how technology properties and users’ awareness on technology security shape team members’ knowledge sharing practice

Acquiring Experiences: An Investigation of the Materialist in Liquid Consumption

Knowledge-based economies and digital disruption in Western societies have triggered significant changes in the way consumers purchase, communicate and maintain relationships. The shift in consumption patterns reflects a move from solid (physical, ownership-based) consumption to more liquid (ephemeral, access-based) consumption. Increased liquidity can affect need fulfillment and consumption goal achievement across individual values, such as materialism. Materialistic consumers obtain possessions to communicate a successful image, achieve happiness or find enjoyment. The dissertation asks, how are materialistic consumers meeting their needs in the digital realm as liquid consumption increases? A mixed methods approach addresses the proposition that social media may allow consumers, including high materialists, to achieve certain consumption goals they once achieved with solid consumption. Qualitative depth interviews and quantitative cross sectional data examine the degree to which Instagram followers experience parasocial relationships with influencers, connect with an influencer’s human brand or feel a psychological sense of community among other followers. The studies also provide insight on whether followers who perceive the relationships and connections will likely purchase brands that influencers post. A final multi-group analysis addresses whether the rise of consumer self-definition through experiences prompts materialistic consumers to participate in the activities and places they see influencers feature. Results reveal that engaging in parasocial relationships with influencers, connecting with an influencer’s human brand and feeling a psychological sense of brand community among other followers all occur to some extent across individuals. The studies also suggest the occurrence of influencer-inspired purchases of both material and experiential nature. While the strength of a parasocial relationship fails to positively affect a follower’s purchase intentions, self-human brand connection strongly influences both types of purchase intentions. Psychological sense of brand community positively influences a follower’s material purchase intentions but not experiential purchase intentions. The extent to which a follower embraces materialism as a personal value makes little difference regarding whether relationships and connections with influencers increase the likelihood of a follower’s material or experiential purchases. The dissertation extends the application of liquid consumption and lends insight to managers engaged in tactics such as influencer and experiential marketing

Socio-technical systems and trust transfer in live streaming e-commerce: analyzing stickiness and purchase intentions with SEM-fsQCA

Live streaming has gained substantial significance in the e-commerce realm, attracting the attention of scholars due to its profound impact on the consumer decision-making journey. However, previous studies have not sufficiently investigated into the complex of marketing strategies through trust transfer mechanisms and socio-technical aspects, considering the dynamic nature of the live streaming e-commerce environment. Grounded on the socio-technical system theory, this research develops a research framework that centers on the exploration of interactivity, entertainment, and visualization as catalysts for trust transfer in live streaming. Trust transfer is conceptualized as advancing from cognitive trust to affective trust. Cognitive trust is proposed as a mediating factor bridging socio-technical system constructs to affective trust, ultimately shaping stickiness behavior and purchase intention in the live streaming context. To test the hypotheses, this study collected data from 682 participants in Indonesia and employed a hybrid analysis approach, combining SEM and fsQCA. The SEM results confirm that socio-technical system constructs significantly predict cognitive trust but do not directly impact affective trust. Instead, cognitive trust plays a full mediating role in transforming trust rooted in emotional bonds within the live streaming environment. Furthermore, both cognitive and affective trust exhibit a significant influence on the formation of stickiness behavior and the driving of purchase intention in the domain of live streaming e-commerce. The findings from fsQCA validate diverse configurations that shape stickiness behaviors and purchase intention, enriching marketing and communication strategies within the live streaming context. Additionally, the fsQCA configurations suggest varying conditions for high and low desired outcomes in stickiness and purchase intention, offering a comprehensive understanding of consumer behavior in live streaming e-commerce. This research makes substantial contributions to both theoretical understanding and marketing practice by providing an extensive discussion of configuration combinations that offer enhanced insights into the study's findings

Studying Users Interactions and Behavior In Social Media Using Natural Language Processing

Social media platforms have been growing at a rapid pace, attracting users\u27 engagement with the online content due to their convenience facilitated by many useful features. Such platforms provide users with interactive options such as likes, dislikes as well as a way of expressing their opinions in the form of text (i.e., comments). As more people engage in different social media platforms, such platforms will increase in both size and importance. This growth in social media data is becoming a vital new area for scholars and researchers to explore this new form of communication. The huge data from social media has been a massive aid to researchers in the mission of exploring the public\u27s behavior and opinion pursuing different venues in social media research. In recent years, social media platforms have facilitated the way people communicate and interact with each other. The recent approach in analyzing the human language in social media has been mostly powered by the use of Natural Language Processing (NLP) and deep learning techniques. NLP techniques are some of the most promising methods used in social media analyses, including content categorization, topic discovery and modeling, sentiment analysis. Such powerful methods have boosted the process of understanding human language by enabling researchers to aggregate data relating to certain events addressing several social issues. The ability of posting comments on these online platforms has allowed some users to post racist and obscene contents, and to spread hate on these platforms. In some cases, this kind of toxic behavior might turn the comment section from a space where users can share their views to a place where hate and profanity are spread. Such issues are observed across various social media platforms and many users are often exposed to these kinds of behaviors which requires comment moderators to spend a lot of time filtering out these inappropriate comments. Moreover, such textual inappropriate contents can be targeted towards users irrespective of age, concerning a variety of topics not only controversial, and triggered by various events. Our work is primarily focused on studying, detecting and analyzing users\u27 exposure to this kind of toxicity on different social media platforms utilizing state-of-art techniques in both deep learning and natural language processing areas, and facilitated by exclusively collected and curated datasets that address various domains. The different domains, or applications, benefit from a unified and versatile pipeline that could be applied to various scenarios. Those applications we target in this dissertation are: (1) the detection and measurement of kids\u27 exposure to inappropriate comments posted on YouTube videos targeting young users, (2) the association between topics of contents cover by mainstream news media and the toxicity of the comments and interactions by users, (3) the user interaction with, sentiment, and general behavior towards different topics discussed in social media platforms in light of major events (i.e., the outbreak of the COVID-19 pandemic). Our technical contribution is not limited to only the integration of the various techniques borrowed from the deep learning and natural language processing literature to those new and emerging problem spaces, for socially relevant computing problems, but also in comprehensively studying various approaches to determine their feasibility and relevant to the discussed problems, coupled with insights on the integration, as well as a rich set of conclusions supported with systematic measurements and in-depth analyses towards making the online space safer

“It’s cool to feel sad”: A thematic analysis of the social media experiences of university students who have self-harmed

Background: Suicide and self-harm rates amongst young people have been identified as a public mental health concern with emerging links to social media use. Aim: The current study aimed to qualitatively explore the social media experiences of university students who have self-harmed, as they have been identified as a group vulnerable to suicide. Method: Semi-structured interviews were completed at two time points with students aged 21 and under who have self-harmed whilst at university, with transcripts of interviews analysed using reflexive thematic analysis (Braun & Clarke, 2021). Results: Three organising themes were identified: 1) Instagram vs reality, 2) A double-edged sword, 3) Curating online spaces. The analysis provided a developmental overview of patterns across students’ experiences online, identifying negative social comparisons, the romanticisation of mental illness, and the development of their insight and rules to engage with social media in a helpful way. Conclusions: The study provided an insight into the evolution of the online lives of students who have self-harmed, highlighting key modifiable risk factors that researchers, policymakers and clinicians could meaningfully target to promote ‘digital hygiene’ and the reduction of potential harm from social media