ABSTRACT
During the COVID-19 pandemic, some research that otherwise would have been conducted in person pivoted to online platforms. This poster paper describes lessons learned from an online study of information behavior by individuals with long-term information needs, focusing on what was learned about how to conduct such a study online. Broadly, three themes are evident: (1) Trust mechanisms were weaker than would be expected for an in-person study, resulting in greater coordination difficulties;(2) What seemed to be a fair reimbursement rate appears to have provided an outsized incentive for fraud;and (3) Zoom proved to be sufficiently capable as a platform for remote use of software for a study that had not originally been designed with remote use in mind. 85th Annual Meeting of the Association for Information Science & Technology ;Oct. 29 – Nov. 1, 2022 ;Pittsburgh, PA. Author(s) retain copyright, but ASIS&T receives an exclusive publication license.
ABSTRACT
Identification of a small group of individuals based on their maximal influence cascade is influence maximization. During the COVID-19 pandemic, discussion forums on the Massive Open Online Course (MOOC) platform have become a paramount interaction medium among learners, and the identification of influential learners evolved as a substantial research issue. In this research paper, an optimization function based on an independent cascade is established for the discussion forum influence maximization problem. A modified version of the BAT algorithm is proposed which memorizes the bad experience of the BAT. The proposed Modified algorithm helps the BAT to remember the worst location that has already been traversed for a reliable estimation in an optimized manner while exploring the best solution. Further, the performance of BAT and Modified BAT for influence maximization on the discussion forum network of a MOOC platform is evaluated which shows the excellent performance of modified BAT. Convergence graph for different populations on deviating probability depicts the effective performance of modified BAT over generic BAT algorithm. © 2022 ACM.
ABSTRACT
The threat of COVID-19 maximizes the demands for live video streaming. How to provide a video streaming service with low latency becomes one urgent and necessary research issue. This paper would survey and discuss the critical factors to impact transmission latency from the perspective of software implementation of a web streaming engine. Based on the initial experiment, the proposed live video web streaming engine can achieve under 3-second latency. © 2022 IEEE.
ABSTRACT
A service (social) robot is defined as the Internet of Things (IoT) consisting of a physical robot body that connects to one or more Cloud services to facilitate human-machine interaction activities to enhance the functionality of a traditional robot. Many studies found that anthropomorphic designs in robots resulted in greater user engagement. Humanoid service robots usually behave like natural social interaction partners for human users, with emotional features such as speech, gestures, and eye-gaze, referring to the users’ cultural and social background. During the COVID-19 pandemic, service robots play a much more critical role in helping to safeguard people in many countries nowadays. This paper gives an overview of the research issues from technical and social-technical perspectives, especially in Human-Robot Interaction (HRI), emotional expression, and cybersecurity issues, with a case study of gamification and service robots. © 2022, Springer Nature Switzerland AG.