Уровень 0 · материалов: 4
В кластер включаются документы, посвященные методам сбора и техническому анализу данных сообщества Habr, и исключаются материалы, не касающиеся данного конкретного ресурса.
Общие признаки: веб-скрейпинг данных Habr, статистический анализ поведения пользователей, анализ контента и популярности
Группа выше: Опросы и статистика сообщества
Смысл: The text demonstrates a comprehensive technical workflow for extracting, processing, and analyzing large amounts of data from the Habr community using Wolfram Language. It aims to provide statistical insights into user behavior, content trends, and hub relationships.
A technical guide and case study demonstrating how to scrape and statistically analyze 62,000 Habr articles using Wolfram Mathematica.
Смысл: The main idea is to demonstrate how the R language can be used for web scraping and statistical data analysis, specifically using the HabraHabr community as a case study to uncover patterns in user behavior and content popularity.
A technical guide on using R to scrape HabraHabr data and perform statistical analysis on post ratings and user behavior.
Смысл: The text is a data-driven study of the Habrahabr social network's growth and user behavior, aiming to uncover patterns and anomalies through independent data collection and analysis.
An independent statistical study of Habrahabr's first six years, analyzing user activity, content ratings, and platform anomalies via custom web-scraping.
Смысл: The text demonstrates how basic web scraping and data analysis can reveal the sociological dynamics of an online community, highlighting the 'Pareto-like' distribution of user activity and the habitual patterns of content consumption.
A Python-based analysis of 2019 Habr comments reveals that a tiny fraction of users create most of the content and that activity peaks during working hours.