graph analysis | BestHub

Xiaohongshu Tech REDtech

Nov 30, 2022 · Information Security

Best Practices for Community and E‑commerce Fraud Prevention on Xiaohongshu: Understanding and Combating Fake Traffic

The article outlines Xiaohongshu’s comprehensive anti‑fraud strategy—defining fake traffic, exposing three service‑provider models, detailing identification and governance challenges, and recommending engine‑based risk‑control, a five‑step process, and AI‑driven behavior, clustering, and graph analyses that have already eliminated billions of fraudulent likes.

anti-fraude‑commerce securityfraud detection

0 likes · 22 min read

Best Practices for Community and E‑commerce Fraud Prevention on Xiaohongshu: Understanding and Combating Fake Traffic

Big Data Technology Architecture

Jul 2, 2022 · Fundamentals

Indirect Shareholding Ratio Calculation Using Graph Techniques

This article explains how to compute indirect shareholding ratios between companies by generating synthetic relationship data, cleaning and normalizing it with multiprocessing, constructing a weighted directed graph using NetworkX, and applying a matrix‑based algorithm to derive the final ownership matrix.

Data ProcessingNetworkXPython

0 likes · 7 min read

Indirect Shareholding Ratio Calculation Using Graph Techniques

High Availability Architecture

Jul 12, 2018 · Information Security

Evolution of Zhihu’s Anti‑Cheat System “Wukong”: Architecture, Strategies, and Lessons Learned

This article chronicles the three‑generation evolution of Zhihu’s anti‑cheat platform Wukong, detailing its business context, spam taxonomy, multi‑layered control methods, architectural redesigns, strategy language improvements, graph‑based risk analysis, and the continuous integration of big‑data and machine‑learning techniques to combat content and behavior spam.

Big DataInformation Securityanti-cheat

0 likes · 23 min read

Architect

Nov 9, 2015 · Big Data

Modeling User Relationships and Information Propagation on Weibo

The article presents a comprehensive analysis of Weibo's social graph, introducing metrics such as propagation power, intimacy, fan and follow similarity, two‑degree relationships, and relationship circles to model and quantify user interactions and information diffusion within the platform.

Big DataPropagationUser Relationship

0 likes · 13 min read

Modeling User Relationships and Information Propagation on Weibo