Poster Session
All posters will be hung in Room 9 (Galerie Dumas D617)
The Virtual Water Cooler
Poster Session Kelsey Zook
The onset of the COVID-19 pandemic caused a drastic shift in many organizations’ communication styles. Businesses had to adapt to the pandemic regulations which resulted in a majority of employees moving into a virtual work environment. The study conducted 15 semi-structured interviews to draw from the experiences professional employees have had while working within a virtual environment to explore how cross-departmental informal communication can lead to a more substantial online presence across an organization’s shared virtual environment. Additionally, the study examined how organizational employees communicate shared experiences through computer-mediated communication. Previous research has been done surrounding individuals communicating through computer-mediated communication, moreover, centered in the workplace. Furthermore, researchers found four themes present: participants experienced negative emotions towards working from home, identifying limitations faced within a virtual environment, specifically a need for personal connection, participants seeking out informal communication, and benefits from engaging in informal communication.
Small Newsrooms, Big Changes: Exploring the Effects of Generative AI
Poster Session Stuart Duncan
This research explores the use of generative AI, specifically chatbots, in small newsrooms and addresses motivations, challenges, and ethical considerations. The study includes developing an open-source chatbot prototype informed by semi-structured interviews with staff from small newsrooms, aiming to create a functional, accessible tool for organizations with limited budgets and technical resources. AI has already reshaped journalism, from personalized news feeds to automated reporting, yet small newsrooms often lack the resources to integrate these technologies. This project examines the potential divide between large and small organizations in AI access, particularly since generative AI tools like ChatGPT have popularized these systems. By leveraging the Unified Theory of Acceptance and Use of Technology (UTAUT), the study analyzes small newsrooms’ views on AI, specifically generative AI’s impact on journalism and audience relationships. The methodology follows Design Research Science Methodology (DRSM) principles, involving three phases: developing an initial chatbot prototype, conducting interviews to gather newsroom feedback, and refining the chatbot and creating an implementation framework. Currently, interviews are underway, with analysis to follow, focusing on adoption motivators like performance expectancy, effort expectancy, social influence, and facilitating conditions. The final open-source prototype and framework will support small newsrooms in adopting AI ethically and effectively, made accessible via GitHub.
Cultural Capital in Digital Spaces - the New Social Media Divide: Examining How Socioeconomic Status Shapes Digital Culture and Participation in Urban Communities
Poster Session Hanfang Sheng
The democratizing promise of social media platforms remains contested in an era of increasing digital disparity. This study investigates the intersection of socioeconomic status and social media engagement in New York City's diverse urban landscape. Through qualitative analysis of 50 semi-structured interviews with participants across varied income levels, we examine how social class shapes digital participation and opportunity. The research framework addresses three critical aspects: technical accessibility, algorithmic visibility, and social capital development. Our findings reveal that despite comparable time spent on platforms, users from lower socioeconomic backgrounds encounter significant obstacles in translating social media presence into tangible professional benefits. Key barriers include varying levels of digital competency, inconsistent internet infrastructure, and algorithmic systems that inadvertently favor users from privileged backgrounds. The study documents how participants from lower socioeconomic strata consistently report reduced content reach, limited networking capabilities, and restricted access to career advancement opportunities. Grounded in Digital Divide Theory and Network Society frameworks, our analysis suggests that social media ecosystems may be reinforcing offline socioeconomic stratification through technical and algorithmic mechanisms. Drawing from successful digital equity initiatives, we propose targeted interventions including community-based digital skill programs, expanded public internet infrastructure, and transparent algorithmic accountability measures. These findings offer valuable insights for platform developers, policymakers, and digital equity advocates working to create more inclusive online spaces.
Synthetic Politics: Deepfakes, Power, and the Crisis of Trust Online
Poster Session Mina Momeni
Political misinformation spreads rapidly through social media, undermining trust, dividing society, and disrupting individuals’ understanding of political events. Deepfakes are AI-generated synthetic media that typically manipulate or replace faces and voices to create highly realistic but often deceptive content. Although this technology has been used for entertainment, it is increasingly deployed to spread misinformation. The study of political deepfakes remains relatively new and underexplored. This study examines public responses to a viral deepfake of former U.S. Vice President Kamala Harris featured in a campaign ad shared by Elon Musk on X (formerly Twitter). By using a combination of quantitative and qualitative content analysis, this research analyzes replies to Musk’s post, which received over 130 million views, 242,000 retweets, and 57,000 comments. Comments will be collected using X API V2 for developers. The preliminary findings demonstrate that many users perceived the deepfake as authentic content. By analyzing how audiences interpret and respond to deepfakes in a political context, this study contributes to media literacy and offers insight into the broader implications of synthetic media on democratic discourse.
Kuwaiti Youth and Digital Privacy Polices: How Policy Perceptions Influence Social Media Use
Poster Session Mohammad Alotaibi
This paper investigates the intricate aspects of privacy on social networks, having the investigation to be focused on the degree of control which young users have over their personal data and the implications of monetizing such data by platforms as well as third-party advertisers in a conservative society like Kuwait on using social media. The study seeks to reveal the Kuwaiti youth's attitudes towards social media privacy policies and its impact on their usage. This study applies a quantitative research method to achieve the goals. An online survey was conducted on a total of 1601 Kuwaiti individuals (males and females) through October 9th to November 9th, 2024. The findings of this study reveal a noticeable decline in youth interest in Facebook, with platforms such as WhatsApp, TikTok, and Instagram emerging as more preferred alternatives. Also, the results prove that most Kuwaiti youth aren't really delving into the details of these privacy policies when they join social networking sites. While some do show a bit of awareness or hesitation, this doesn't necessarily mean they're taking concrete actions, like actually reading the whole policy or looking for other options. They likely feel like they don't have a choice since they probably perceive that there is no real alternative. The study suggests that future studies adopt experimental approaches to develop the most user-friendly and comprehensible formulations of privacy policies, ensuring they are easily understood by users.
The Sociotechnical Imaginary of Generative AI Use in Media Production: From Being the New ICT to Reaching the Obligatory Passage Point
Poster Session Sangya Tyagi
The integration of Generative AI into journalistic production represents a critical juncture in the evolution of contemporary media systems. This study, situated at the intersection of digital media studies and the sociology of technology, interrogates Generative AI from the perspective of Actor-Network Theory, inspecting how Generative AI has inserted itself as the new ICT and is quickly moving to achieve the Obligatory Passage Point status as an actant in the media production networks. Currently through with the first phase of data collection, this research employs a mixed-methods approach that combines an experimental design with survey research and qualitative expert interviews. Interviews with media practitioners and journalists provide insight into institutional logics, professional anxieties, and industry framings of technological change. While the second half of the research dealing with audience perception evaluates media texts for credibility, bias, quality, and trust, all achieved through a double blind survey set as an online experiment, capturing broader attitudes toward AI in journalism. This project fills a significant gap in current scholarship by bridging audience reception studies with critical perspectives on algorithmic media and technological mediation. The primary results reveal how much AI has been integrated in workflows and in the network of media production and dissemination. Empirically, by integrating both public and expert voices, the study foregrounds the uneven and fear mongering nature of information surrounding AI use. Theoretically, the research contributes to debates in the sociology of technology by examining AI as a socio-technical actor that has altered institutional practices and audience relations.
