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The impact of culture on how people express distress in online support communities is increasingly a topic of interest within Computer Supported Cooperative Work (CSCW) and Human-Computer Interaction (HCI). In the United States, distinct…
With the growth of social media and large language models, content moderation has become crucial. Many existing datasets lack adequate representation of different groups, resulting in unreliable assessments. To tackle this, we propose a…
The widespread adoption of social media has heightened interest in its psychological effects, particularly on mental health indicators such as anxiety, depression, loneliness, and sleep quality, as these platforms increasingly influence…
This study examines social media users' preferences for the use of platform-wide moderation in comparison to user-controlled, personalized moderation tools to regulate three categories of norm-violating content - hate speech, sexually…
Modeling interpersonal influence on different sentimental polarities is a fundamental problem in opinion formation and viral marketing. There has not been seen an effective solution for learning sentimental influences from users' behaviors…
The COVID-19 pandemic triggered not only a global health crisis but also an infodemic, an overload of information from diverse sources influencing public perception and emotional responses. In this context, fear emerged as a central…
Collective opinions affect civic participation, governance, and societal norms. Due to the influence of opinion dynamics, many models of their formation and evolution have been developed. A commonly used approach for the study of opinion…
The persistence of lying by some consumers in their online posts of experiences with businesses is problematic, and taints the global pool of information that is used for decision making by people that assume they are true accounts of…
In the aftermath of the financial crisis, the growing literature on financial networks has widely documented the predictive power of topological characteristics (e.g. degree centrality measures) to explain the systemic impact or systemic…
Online marketplace designers frequently run A/B tests to measure the impact of proposed product changes. However, given that marketplaces are inherently connected, total average treatment effect estimates obtained through Bernoulli…
The group recommendation (GR) aims to suggest items for a group of users in social networks. Existing work typically considers individual preferences as the sole factor in aggregating group preferences. Actually, social influence is also an…
Software producers are now recognizing the importance of improving their products' suitability for diverse populations, but little attention has been given to measurements to shed light on products' suitability to individuals below the…
Small and medium-sized enterprises are considered an essential part of the EU economy, however, highly vulnerable to cyberattacks. SMEs have specific characteristics which separate them from large companies and influence their adoption of…
Social media are massive marketplaces where ideas and news compete for our attention. Previous studies have shown that quality is not a necessary condition for online virality and that knowledge about peer choices can distort the…
Online Mental Health Communities (OMHCs), such as Reddit, have witnessed a surge in popularity as go-to platforms for seeking information and support in managing mental health needs. Platforms like Reddit offer immediate interactions with…
Outsourcing of information and communication technologies (ICT) and related services is an established and growing industry. Recent trends, such as the move toward multi-sourcing have increased the complexity and risk of these outsourcing…
The Internet of Behaviors (IoB) is an emerging concept that utilizes devices to collect human behavior and provide intelligent services. Although some research has focused on human behavior analysis and data collection within IoB, the…
Current AI systems minimize risk by enforcing ideological neutrality, yet this may introduce automation bias by suppressing cognitive engagement in human decision-making. We conducted randomized trials with 2,500 participants to test…
Web is often used for finding information and with a learning intention. In this thesis, we propose a study to investigate the process of learning online across varying cognitive learning levels using crowd-sourced participants. Our aim was…
Recent increase in online privacy concerns prompts the following question: can a recommender system be accurate if users do not entrust it with their private data? To answer this, we study the problem of learning item-clusters under local…