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Abstract
On home-sharing platforms like Airbnb, the user-generated data provided by hosts and guests are valuable for user trustworthiness prediction (UTP). They convey not only personal information associated with individual users (e.g., age and gender), but also other social cues (e.g., host-guest homophily). However, user data have an intrinsic property of heterogeneity, which contains various types of entities and connections. Additionally, previous research in UTP primarily focused on users’ personal features, leaving the social features largely unexploited. In this paper, we propose a novel heterogeneous graph framework for UTP. Particularly, we build a Heterogeneous Graph Attention network (HGAT) on a Heterogeneous Information Graph (HIG). The HIG can integrate heterogeneous information from users and capture their interconnections, whilst the HGAT selectively aggregates this information for UTP. Experiments with a real-world Airbnb dataset showed that our method performed better than other cutting-edge methods, demonstrating an effective usage of our framework for UTP.
Original language | English |
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Title of host publication | PACIS 2024 Proceedings |
Publisher | Association for Information Systems |
Publication status | Published - Jul 2024 |
Event | The annual Pacific Asia Conference on Information Systems (PACIS) : 2024 - Ho Chi Minh City, Viet Nam Duration: 1 Jul 2024 → 5 Jul 2024 https://aisel.aisnet.org/pacis2024/ |
Public Lecture
Public Lecture | The annual Pacific Asia Conference on Information Systems (PACIS) : 2024 |
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Abbreviated title | PACIS2024 |
Country/Territory | Viet Nam |
City | Ho Chi Minh City |
Period | 1/07/24 → 5/07/24 |
Internet address |
Funding
The work is supported by LEO Dr David P. Chan Institute of Data Science, the Hong Kong RGC ECS (LU23200223/130393), the Lam Woo Research Fund (LWP20018/871232), the Direct Grant (DR23A9/101194), the Faculty Research Grants (DB23B5/102083 and DB23AI/102070) and the Research Seed Fund (102241) of Lingnan University, Hong Kong.
Keywords
- Home-sharing Platforms (HSPs)
- User Trustworthiness Prediction (UTP)
- Heterogeneous Graph Attention network
- Homophily Graph
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