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From Anomaly Detection to Rumour Detection using Data Streams of Social Platforms

Summary: Multi-modal anomaly detection for rumour detection in streaming social data, combining entity and relation signals. Graph-based scan raises local anomalies to network-level rumours; incremental streaming methods demonstrated on 4M tweets with 1k+ rumours. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11991
Venue
VLDB
Year
2019
Pagerank
5.4622609e-05
Overall Rank
8,227 | 43.56%
DOI
10.14778/3329772.3329778

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{tam_vldb19,
        title = {{From Anomaly Detection to Rumour Detection using Data Streams of Social Platforms}},
        author = {Tam, Nguyen Thanh and Weidlich, Matthias and Zheng, Bolong and Yin, Hongzhi and Hung, Nguyen Quoc Viet and Stantic, Bela},
        journal = {PVLDB},
        series = {{VLDB} '19},
        volume = {12},
        number = {9},
        pages = {1016--1029},
        doi = {10.14778/3329772.3329778},
        url = {https://doi.org/10.14778/3329772.3329778},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
8,230 TOD: GPU-accelerated Outlier Detection via Tensor Operations 2023 VLDB 5.4619615e-05
10,424 ABFlow: Alert Bursting Flow Query in Streaming Temporal Flow Networks 2026 SIGMOD 5.093636e-05
10,919 X-Blossom: Massive Parallelization of Graph Maximum Matching 2025 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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