Conference Agenda (All times are shown in Mountain Daylight Time (MDT) unless otherwise noted)
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Session Chair: Souvick Ghosh, San José State University, USA
Location:Imperial Ballroom 2, Third Floor
Presentations
4:00pm - 4:30pm ID: 323 / PS-07: 1 Long Papers Confirmation 1: I/we acknowledge that all session authors/presenters have read and agreed to the ASIS&T Annual Meeting Policies Topics: Social Media and Social Computing (social media; social media analytics; community informatics; online communities; social informatics; social computing) Keywords: social media, nostalgia, computational social science, detection and analysis, Twitter
Nostalgia on Twitter: Detection and Analysis of a Large-Scale Dataset
Fiona Stanley Jothiraj1, Lingzi Hong2, Afra Mashhadi1
1University of Washington, USA; 2University of North Texas, USA
Nostalgia is a self-conscious social emotion that arises from reminiscence of past memories. Collective nostalgia on social media such as Twitter has been seen as a method to comfort individuals in the status of isolation, fear, and a loss of freedom. In recent years, many studies have focused on offering analysis of nostalgic conversations to understand their impact on various domains including marketing and mental health, but little attention has been given to how to detect such conversations in the first place. This paper offers a novel large-scale nostalgic tweets dataset. We describe our extensive methodology to create and validate this dataset using natural language processing models and Large Language Models to detect nostalgic conversations on Twitter. We demonstrate the properties of this dataset alongside analysis revealing insight into context and patterns of what/how people reminiscence about. We finish the paper by describing other research studies that our dataset enables.
4:30pm - 5:00pm ID: 349 / PS-07: 2 Long Papers Confirmation 1: I/we acknowledge that all session authors/presenters have read and agreed to the ASIS&T Annual Meeting Policies Topics: Social Media and Social Computing (social media; social media analytics; community informatics; online communities; social informatics; social computing) Keywords: Platform Comparison, Crisis Informatics, Climate Change, Multi-modal Analysis, Social Media
Comparing Climate Change Content and Comments Across Instagram Reels, TikTok, and YouTube Shorts and Long Videos
Yiran Duan, Christy Khoury, Una Joh, Alexander Smith, Calvin Cousin, Jeff Hemsley
Syracuse University, USA
Social media plays a vital role as a communication channel for pertinent topics, including climate change. This paper investigates the content and comments of short and long-format videos on Instagram, TikTok, and YouTube to compare climate change discourse on these platforms. Eighty videos and their respective 69,135 comments were collected and analyzed using content analysis, statistical analysis, data visualization, and social network analysis. Our findings show that in our dataset, videos in the short-format (Instagram, TikTok, and YouTube Shorts) provide all sorts of content, while YouTube long videos only focus on educational and activism content. The short-format videos also show different stances towards climate change, such as a climate change denier stance, while YouTube long videos do not. For comments, videos in the short-format had less engagement compared to YouTube long videos. Our findings inform implications for both researchers and social media platform designers.
5:00pm - 5:30pm ID: 420 / PS-07: 3 Long Papers Confirmation 1: I/we acknowledge that all session authors/presenters have read and agreed to the ASIS&T Annual Meeting Policies Topics: Human-Computer Interaction (usability and user experience; human-technology interaction; human-AI interaction; user-centered design) Keywords: Tourism Live Streaming, Socio-Technical Perspective, People-Centered Context, Impulsive Travel Intention, Parasocial Relationship
From Click to Trip: A Socio-Technical Perspective on Tourism Live Streaming
Jiayu Han1, Alton Y.K. Chua1, Shaogui Xu2
1Nanyang Technological University, Singapore; 2Fujian Normal University, People's Republic of China
Tourism live streaming can significantly enhance users’ desire to travel. Although previous studies have identified many technical and social enablers influencing users’ impulsive travel intention, limited research has examined it from a socio-technical perspective. This paper aims to develop and validate a theoretical model that explains how visibility, personalization, and metavoicing influence impulsive travel intention through parasocial relationship in tourism live streaming. Empirical results (N = 551) reveal that visibility, personalization, and metavoicing exert both direct positive impacts on impulsive travel intention and indirect effects through the mediation of parasocial relationship. This paper also identifies gender as a moderating role in the proposed model. This paper enriches the literature by not only shedding light on the underlying process through which users develop impulsive travel intention, considering both technical features and social interaction but also stands as one of the earliest to investigate the gender’s moderating role in this process.
