# iphysresearch/TOP250movie_douban

TOP250豆瓣电影短评：Scrapy 爬虫+数据清理/分析+构建中文文本情感分析模型

Repository: https://github.com/iphysresearch/TOP250movie_douban
Canonical: https://ross.abutalabs.com/products/top250movie_douban
Language: Jupyter Notebook
License: BSD-2-Clause
License Family: permissive
Topics: project
Last push: 2022-07-23T06:46:00+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3021, "days_push": 1502, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1022, forks 200 (observed 2026-08-28T04:03:16.064854+00:00)

## What it is
A Jupyter Notebook-based educational project that scrapes Douban Top 250 movie short reviews with Scrapy, then performs data cleaning, statistical analysis, visualization, and builds Chinese text sentiment classification models (Naive Bayes, SVM, fastText, CNN, RNN, GRU). It serves as an end-to-end data science project example.

## Use cases
- learn web scraping with scrapy
- chinese sentiment analysis example
- analyze douban movie reviews
- text classification tutorial with cnn rnn
- data cleaning and visualization practice project
- build a naive bayes text classifier

## When to choose
- learning the full pipeline from scraping to NLP modeling
- studying Chinese text classification with multiple model approaches
- looking for a complete data science project example

## When to avoid
- production web scraping of Douban at scale
- a maintained sentiment analysis library
- non-Chinese text analysis

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: web-scraping, nlp, data-science, data-visualization, machine-learning
- domain: data-science, crawlers, tutorials
- platform: python
- tags: scrapy, sentiment-analysis, chinese-text, douban, jupyter-notebook, text-classification, word-cloud, natural-language-processing

## Member repositories
- iphysresearch/TOP250movie_douban (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:16.064854+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:08:44.714318+00:00, confidence not recorded.
  - readme: https://github.com/iphysresearch/TOP250movie_douban (fetched 2026-08-28T04:03:16.064854+00:00, sha e605f2cb4047)
- Data as of 2026-08-30T08:39:29.467469+00:00.