Уровень 0 · материалов: 4
В кластер входят документы, посвященные техническим методам представления и анализа структур связей в виде графов, и не входят документы, не касающиеся сетевого анализа.
Общие признаки: анализ социальных связей, визуализация графов, построение сетей взаимоотношений, инструменты работы с графовыми данными
Группа выше: Визуализация графов и сетевых связей
Смысл: The text explores the practical application of the small-world phenomenon within a specific social network to demonstrate how interconnected people are, while also addressing the technical challenges of pathfinding in large graph databases.
An author uses a custom script and community help to map friendship chains on VKontakte, proving connections to Pavel Durov and seeking an optimized algorithm for large-scale graph pathfinding.
Смысл: The text serves as a technical guide and review of the NetworkX Python library, highlighting its versatility in managing complex graphs for scientific research, education, and data analysis.
An overview of the NetworkX Python library, covering its graph types, performance, data structures, and visualization capabilities for network analysis.
Смысл: The text describes a data visualization project that maps the geographic distribution of friendships among 10 million Facebook users using Apache Hive and GNU R, illustrating the global nature of social connections.
A Facebook intern used Apache Hive and GNU R to analyze and visualize the geographic connections of 10 million users, creating a global map of friendships.
Смысл: The text demonstrates the power of the Wolfram Language by performing a deep quantitative analysis of 'Game of Thrones' data, creating complex visualizations of character relationships, screen time, dialogue, and movements across Westeros.
A technical tutorial using Wolfram Language to create complex infographics about Game of Thrones characters, locations, and actors.