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The iConference Awards recognize the most exceptional research papers and posters presented at the iConference each year. They are judged by the respective track chairs, in consultation with the conference and program chairs.

The winners were announced at iConference 2024.

Best Full Research Paper Award

Winner and Finalists

Click on the arrows to see all finalists in order of IDs.

(415) What motivates you to use VR exergames to substitute for real sports? — An empirical study based on technology readiness and technology acceptance model

Haodong Sun, Qing Ke

Nanjing University, China, People's Republic of

Virtual reality technology has brought about a new way of exercising through VR exergames. A critical and interesting question is whether users are willing to use VR exergames as an effective supplement to traditional exercise methods, or even as a complete substitute for some real sports. In this study, we aim to identify the factors that affect users' perception of VR exergames and intention to substitute them for real sports based on the Technology Readiness and Acceptance Model (TRAM). The proposed model and 16 hypotheses were tested by structural equation analysis using 248 validated questionnaires. Our results suggest that users' technological readiness and perceived interactivity significantly impact their perception of VR exergames and intention to substitute real sports. Perceived usefulness had a significant impact on substitution intention, while perceived ease of use not. Our findings provide important recommendations for future VR exergames development to enhance user experience and promote national fitness.

Best Full Paper
Image by Wan San Yip

Award for Best Short Research Paper

Winner and Finalists

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Best Short Paper

(434) A problematic dichotomy in the perspective of field theory: hermeneutics and quantitative analysis in distant reading

Mozhuo Chen

Fudan University, China

Moretti’s “distant reading” is regarded as a pioneer and an exemplar of computational literary studies. “Distant reading” puts forward a strict boundary between hermeneutics and quantitative analysis. The relationship between the two and the nature of quantitative analysis in literary studies are key issues in the theory of computational literary studies. This paper analyzes the claims and issues behind Moretti’s dichotomy, and introduces Bourdieu’s field theory perspective, pointing out that the nature of quanti-tative analysis must be understood in relation to the larger disciplinary discursive practices in which it is embedded.

Award for Best Poster

Winner and Finalists

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(137) Shaping the community identity of digital humanities: A global investigation on scholar composition of digital humanities centers

Zhiwei Hu¹⁺², Jiangfeng Liu¹⁺², Lei Pei¹⁺²

1: Laboratory of Data Intelligence and Interdisciplinary Innovation, Nanjing University, China, People's Republic of; 2: School of Information Management, Nanjing University, China, People's Republic of

Digital humanities (DH) is an evolving field fostering interdisciplinary col-laboration, with an impressive engagement of library and information sci-ence (LIS). To assess how DH is situated in the academic landscape and bridge the gap between DH and LIS, it is essential to undertake a comprehen-sive global investigation of the DH community, thereby gaining insights into its current identity. In this study, we examined the scholar composition of 129 digital humanities centers (DHCs) under a disciplinary classification scheme, and further explored the characteristics of the global DH community using methods of diversity measures and community detection. Our findings reveal that beyond traditional humanities, a diverse range of disciplines con-tributes to DH research and practice. Particularly noteworthy are the roles played by LIS and computer science, serving as two main sources of compu-tational expertise. Based on the congruence of community identities, it is im-perative for LIS, who has established a prominent presence within the DH field, to proactively connect to and embrace DH as a vital source of growth in its own domain.

Best Poster

Award for Best Chinese Research Paper

Winner and Finalists

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(153) Research on Early Identification of Emerging Topics Based on the Three-Dimensional Framework for Weak Signals

Jin Mao¹, Ming Ma², Gang Li¹, Shuxuan Xiang²

1: Center for Studies of Information Resources, Wuhan University
2: Laboratory of Data Intelligence and Interdisciplinary Innovation, Nanjing University

In the constantly evolving landscape of information and innovation, the ability to accurately predict emerging topics is vital across various fields. This study regards weak signals as the early stages of emerging topics and identifies these nascent topics through an innovative three-dimensional analysis framework for weak signals. Initially, we construct a keyword citation network, identifying novel signal collections based on changes in network structure. We then conduct a temporal analysis of the visibility and diffusion of signals with time-weighted attributes to identify weak signals, consider their social influence, and quantify the influence of weak signals from the public perception perspective using alternative metrics. Finally, an evaluation framework for emerging topics based on weak signals is built across three dimensions: visibility, diffusion, and influence. We applied the method to gene editing and underwent multi-angle method verification and comparative analysis. The results demonstrate that this approach not only enhances the capability to identify emerging topics at an early stage and grasp their development trends but also enables the identification of emerging topics with significant social impact, thereby offering valuable insights for strategic decision-making, innovation management, and future foresight.

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