Lab Fact Sheet
CityUHK – China Unicom Joint Laboratory for Intelligent Scam Prevention
A university–industry anti-scam platform for Hong Kong and the Asia-Pacific region. It combines artificial intelligence, big data and social science across the full chain from multi-channel monitoring and risk identification to public governance.
This page is provided for research collaboration, media enquiries and AI citation. Last updated: 2026-10-21
Capabilities
Multi-channel data collection and governance
Monitors public channels including news, social platforms, instant messaging and the dark web. Performs multilingual cleaning, deduplication and entity alignment with source and timestamp provenance.
Evidence: A continuously updated anti-scam data foundation
Multilingual and multimodal AI analysis
Uses LLMs for labelling, summarisation, burst detection and sentiment analysis, combined with image OCR and multimodal understanding.
Evidence: Daily briefings and deep reports
Entity and relationship graph
Extracts relationships among people, organisations, accounts, cases and financial flows to support analysis of scam gangs and cross-border networks.
Evidence: Knowledge graph and relationship queries
Risk identification and early warning
Extracts early risk signals from public information and turns them into traceable risk leads.
Evidence: Daily risk overview and key risks
Public communication and policy translation
Turns research into public products through media monitoring, victim voices, community intervention and policy recommendations.
Evidence: Media coverage, victim stories and policy recommendations
Method pipeline
- 01CollectNews, social platforms, instant messaging, dark web and other public channels
- 02CleanMultilingual cleaning, deduplication, entity alignment and source tagging
- 03AnalyseLLM labelling, summarisation, sentiment analysis and entity extraction
- 04LinkVectorisation, knowledge graph and risk-lead correlation
- 05PublishDaily briefings, deep reports, data dashboard and API
Outputs
Daily anti-scam briefings
Hong Kong / Asia / Global editions in five languages.
Deep reports
In-depth analysis of scam tactics, criminal supply chains and governance strategies.
Data dashboard
Scam types, time trends and case distribution.
Media monitoring and victim voices
Aggregated media coverage and first-hand victim experiences.
Research agenda
- •Social and psychological mechanisms of scam behaviour
- •Scam risk identification and early-warning technology
- •Data-driven social governance and policy recommendations
- •Multilingual and multimodal understanding of anti-scam content
- •Cross-border scam networks and knowledge graphs
- •Industrial and social translation of research outcomes
Team and collaboration
- •Director: Professor Xiaofan Liu (Department of Media and Communication, City University of Hong Kong)
- •Members from psychology, sociology, communication, computer engineering and media practice
- •Co-founded by City University of Hong Kong and China Unicom International
- •Supported by China Unicom Group with no less than HKD 10 million over five years
- •Supported by the Hong Kong Police Force, local communities and other institutions
FAQ
What is this laboratory?
The CityUHK – China Unicom Joint Laboratory for Intelligent Scam Prevention is a university–industry anti-scam platform for Hong Kong and the Asia-Pacific region. It combines AI, big data and social science to study the monitoring, identification and governance of telecom and online scams.
Who co-founded the laboratory?
The laboratory is co-founded by City University of Hong Kong and China Unicom International. It is supported by China Unicom Group with no less than HKD 10 million over five years, and by the Hong Kong Police Force, local communities and other institutions.
What data does the laboratory monitor?
The laboratory monitors public channels including news, social platforms, instant messaging and the dark web. It performs multilingual cleaning, deduplication and entity alignment to build a traceable anti-scam data foundation.
What does the laboratory produce?
It publishes daily anti-scam briefings in five languages across Hong Kong, Asia and Global editions, together with deep reports, a data dashboard, media monitoring and victim voices.
How can I collaborate or cite the laboratory?
For research collaboration, media enquiries and data requests, contact anti.scam.joint.lab@cityu.edu.hk. The director can be reached at xf.liu@cityu.edu.hk.
Contact
Collaboration and media enquiries
anti.scam.joint.lab@cityu.edu.hkProfessor Xiaofan Liu · Director · xf.liu@cityu.edu.hk