TY  - CHAP
A1  - Krasnova, Hanna
A1  - Gundlach, Jana
A1  - Baumann, Annika
T1  - Coming back for more
BT  - the effect of news feed serendipity on social networking site sage
T2  - PACIS 2022 proceedings
N2  - Recent spikes in social networking site (SNS) usage times have launched investigations into reasons for excessive SNS usage. Extending research on social factors (i.e., fear of missing out), this study considers the News Feed setup. More specifically, we suggest that the order of the News Feed (chronological vs. algorithmically assembled posts) affects usage behaviors. Against the background of the variable reward schedule, this study hypothesizes that the different orders exert serendipity differently. Serendipity, termed as unexpected lucky encounters with information, resembles variable rewards. Studies have evidenced a relation between variable rewards and excessive behaviors. Similarly, we hypothesize that order-induced serendipitous encounters affect SNS usage times and explore this link in a two-wave survey with an experimental setup (users using either chronological or algorithmic News Feeds). While theoretically extending explanations for increased SNS usage times by considering the News Feed order, practically the study will offer recommendations for relevant stakeholders.
Y1  - 2022
UR  - https://aisel.aisnet.org/pacis2022/271
SN  - 9781958200018
PB  - AIS Electronic Library (AISeL)
CY  - [Erscheinungsort nicht ermittelbar]
ER  - 
TY  - CHAP
A1  - Sultanow, Eldar
A1  - Chircu, Alina
A1  - Wüstemann, Stefanie
A1  - Schwan, André
A1  - Lehmann, Andreas
A1  - Sept, André
A1  - Szymaski, Oliver
A1  - Venkatesan, Sripriya
A1  - Ritterbusch, Georg David
A1  - Teichmann, Malte Rolf
T1  - Metaverse opportunities for the public sector
T2  - International Conference on Information Systems 2022 : Special Interest Group on Big Data : Proceedings
N2  - The metaverse is envisioned as a virtual shared space facilitated by emerging technologies such as virtual reality (VR), augmented reality (AR), the Internet of Things (IoT), 5G, artificial intelligence (AI), big data, spatial computing, and digital twins (Allam et al., 2022; Dwivedi et al., 2022; Ravenscraft, 2022; Wiles, 2022). While still a nascent concept, the metaverse has the potential to “transform the physical world, as well as transport or extend physical activities to a virtual world” (Wiles, 2022). Big data technologies will also be essential in managing the enormous amounts of data created in the metaverse (Sun et al., 2022). Metaverse technologies can offer the public sector a host of benefits, such as simplified information exchange, stronger communication with citizens, better access to public services, or benefiting from a new virtual economy. Implementations are underway in several cities around the world (Geraghty et al., 2022). In this paper, we analyze metaverse opportunities for the public sector and explore their application in the context of Germany’s Federal Employment Agency. Based on an analysis of academic literature and practical examples, we create a capability map for potential metaverse business capabilities for different areas of the public sector (broadly defined). These include education (virtual training and simulation, digital campuses that offer not just online instruction but a holistic university campus experience, etc.), tourism (virtual travel to remote locations and museums, virtual festival participation, etc.), health (employee training – as for emergency situations, virtual simulations for patient treatment – for example, for depression or anxiety, etc.), military (virtual training to experience operational scenarios without being exposed to a real-world threats, practice strategic decision-making, or gain technical knowledge for operating and repairing equipment, etc.), administrative services (document processing, virtual consultations for citizens, etc.), judiciary (AI decision-making aids, virtual proceedings, etc.), public safety (virtual training for procedural issues, special operations, or unusual situations, etc.), emergency management (training for natural disasters, etc.), and city planning (visualization of future development projects and interactive feedback, traffic management, attraction gamification, etc.), among others. We further identify several metaverse application areas for Germany's Federal Employment Agency. These applications can help it realize the goals of the German government for digital transformation that enables faster, more effective, and innovative government services. They include training of employees, training of customers, and career coaching for customers. These applications can be implemented using interactive learning games with AI agents, virtual representations of the organizational spaces, and avatars interacting with each other in these spaces. Metaverse applications will both use big data (to design the virtual environments) and generate big data (from virtual interactions). Issues related to data availability, quality, storage, processing (and related computing power requirements), interoperability, sharing, privacy and security will need to be addressed in these emerging metaverse applications (Sun et al., 2022). Special attention is needed to understand the potential for power inequities (wealth inequity, algorithmic bias, digital exclusion) due to technologies such as VR (Egliston & Carter, 2021), harmful surveillance practices (Bibri & Allam, 2022), and undesirable user behavior or negative psychological impacts (Dwivedi et al., 2022). The results of this exploratory study can inform public sector organizations of emerging metaverse opportunities and enable them to develop plans for action as more of the metaverse technologies become a reality. While the metaverse body of research is still small and research agendas are only now starting to emerge (Dwivedi et al., 2022), this study offers a building block for future development and analysis of metaverse applications.
Y1  - 2022
UR  - https://aisel.aisnet.org/sigbd2022/5/
PB  - AIS
CY  - Atlanta
ER  - 
TY  - CHAP
A1  - Hagemann, Linus
A1  - Abramova, Olga
T1  - Crafting audience engagement in social media conversations
BT  - evidence from the U.S. 2020 presidential elections
T2  - Proceedings of the 55th Hawaii International Conference on System Sciences
N2  - Observing inconsistent results in prior studies, this paper applies the elaboration likelihood model to investigate the impact of affective and cognitive cues embedded in social media messages on audience engagement during a political event. Leveraging a rich dataset in the context of the 2020 U.S. presidential elections containing more than 3 million tweets, we found the prominence of both cue types. For the overall sample, positivity and sentiment are negatively related to engagement. In contrast, the post-hoc sub-sample analysis of tweets from famous users shows that emotionally charged content is more engaging. The role of sentiment decreases when the number of followers grows and ultimately becomes insignificant for Twitter participants with a vast number of followers. Prosocial orientation (“we-talk”) is consistently associated with more likes, comments, and retweets in the overall sample and sub-samples.
KW  - mediated conversation
KW  - big data
KW  - engagement
KW  - sentiment analysis
KW  - social media
Y1  - 2022
SN  - 978-0-9981331-5-7
SP  - 3222
EP  - 3231
PB  - HICSS Conference Office University of Hawaii at Manoa
CY  - Honolulu
ER  -