Explainable Visualization of Collaborative Vandal Behaviors in Wikipedia
| Autor: | Zerong Liu, Siva Sandeep Subramanian, Parab Pushparaj, Aidong Lu |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Creative visualization
Interface (Java) Computer science media_common.quotation_subject 020207 software engineering 0102 computer and information sciences 02 engineering and technology 01 natural sciences Human-centered computing Visualization Multiple data 010201 computation theory & mathematics Human–computer interaction 0202 electrical engineering electronic engineering information engineering Set (psychology) Statistical graphics media_common |
| Zdroj: | VizSEC |
| DOI: | 10.1109/vizsec48167.2019.9161504 |
| Popis: | Online social networks are prone to be targeted by various frauds and attacks, which are difficult to detect due to their complexity and variations. The challenge is to make sense of all information with suitable exploration tools for different groups of users. This project focuses on an explainable visualization approach to study collaborative behaviors of vandal users on Wikipedia. Our approach creates visualization with commonly used techniques from cartography and statistical graphics that are familiar to the general public for effectiveness and explainability. We have built a large-scale visualization system which supports an illustrative interface with multiple data query, filtering, analysis, and interactive exploration functions. Examples and case studies are provided to demonstrate that our approach can be used effectively for a set of Wikipedia behavior analysis tasks. |
| Databáze: | OpenAIRE |
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