Our work “ARTEMIS: Detecting Airdrop Hunters in NFT Markets with a Graph Learning System” is accepted by WWW’24

Airdrops have become a standard tactic in Web3 business operations, with Decentralized Applications (DApps) distributing tokens to encourage user engagement based on smart contract rules. This practice has led to the emergence of “airdrop hunters,” individuals who collect wallet addresses to claim these generous token giveaways by interacting with the contracts. While airdrops are beneficial for attracting early DApp users, the self-trading activities of hunters to appear as active participants threaten the ecosystem’s integrity and challenge the decentralization goals of DApps. DApp teams face the challenge of detecting airdrop hunters without disadvantaging genuine users.

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Our Work “Web3 Metaverse: State-of-the-Art and Vision” Is Accepted By ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)

The metaverse, as a rapidly evolving socio-technical phenomenon, exhibits significant potential across diverse domains by leveraging Web3 (a.k.a. Web 3.0) technologies such as blockchain, smart contracts, and non-fungible tokens (NFTs). This survey aims to provide a comprehensive overview of the Web3 metaverse from a human-centered perspective. We systematically review the metaverse’s industrial (data from Dow Jones Factiva database) and academic (data from Google Scholar website) developments over the past 30 years, highlighting the balanced contributions from its core components: Web3, immersive convergence, and crowd intelligence communities.

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Our Work “MetaCast: A Self-Driven Metaverse Announcer Architecture Based on Quality of Experience Evaluation Model” Is Accepted By ACM MM’ 23

We propose a three-stage architecture for metaverse announcers, which is designed to identify events, position cameras, and blend between shots. Based on the architecture, we introduce a Metaverse Announcer User Experience (MAUE) model to identify the factors affecting the users’ Quality of Experience (QoE) from a human-centered perspective. In addition, we implement MetaCast, a practical self-driven metaverse announcer in a university campus metaverse prototype, to conduct user studies for MAUE model. The experimental results have effectively achieved satisfactory announcer settings that align with the preferences of most users, encompassing parameters such as video transition rate, repetition rate, importance threshold value, and image composition.

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Our work “Altruistic and Profit-oriented: Making Sense of Roles in Web3 Community from Airdrop Perspective” is accepted by ACM CHI’23

Many decentralized applications (DApps) issue airdrops to early supporters for their contributions. However, most eligible users are motivated by financial profit or preferential access to tokens with governance rights to obtain quick cash. In this paper, we take ParaSwap as a representative example, trying to evaluate the Web 3.0 community and the effectiveness of allocation principles through the analysis of eligible users’ behavior and token transaction network.

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Our Work “Metaverse for Social Good : A University Campus Prototye” Has Been Accepted by ACM MM’21

Our recent work “Metaverse for Social Good : A University Campus Prototye” has been accepted by the Brave New Ideas (BNI) track of 29th ACM International Conference on Multimedia (ACM MM 2021). In this paper, we propose a three-layer architecture for metaverse, including infrastructure, interaction, and ecosystem, and the key components in each layer are […]

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