# Zephery/weiboanalysis

微博情感分析，文本分类，毕业设计项目

Repository: https://github.com/Zephery/weiboanalysis
Canonical: https://ross.abutalabs.com/products/weiboanalysis
Language: Python
License: Apache-2.0
License Family: permissive
Topics: adaboost, svm, bayes, machine-learning
Archived: true
Last push: 2020-04-23T09:15:21+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3347, "days_push": 2323, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1088, forks 205 (observed 2026-08-28T04:03:32.576324+00:00)

## What it is
A Python graduation project performing sentiment analysis and text classification on Weibo posts using SVM, Naive Bayes, and AdaBoost. It is explicitly unmaintained and intended as a reference for learning approaches rather than production use.

## Use cases
- sentiment analysis of weibo posts
- chinese text classification with svm and adaboost
- learn how to combine naive bayes with adaboost
- reference for a machine learning graduation project
- pipeline for scraping and classifying social media text

## When to choose
- you want to study the workflow of a sentiment analysis pipeline
- you need example code combining SVM, Bayes, and AdaBoost for Chinese social media text

## When to avoid
- you need a maintained, production-ready sentiment analysis tool
- you require accurate, bug-free code or documentation
- you need modern NLP approaches like transformers

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: machine-learning, nlp
- domain: machine-learning, education
- platform: python
- tags: sentiment-analysis, weibo, text-classification, adaboost, svm, naive-bayes, graduation-project, chinese, natural-language-processing

## Member repositories
- Zephery/weiboanalysis (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:32.576324+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 2026-08-30T06:49:21.061197+00:00, confidence not recorded.
  - readme: https://github.com/Zephery/weiboanalysis (fetched 2026-08-28T04:03:32.576324+00:00, sha fdc851d726ca)
- Data as of 2026-08-30T08:39:29.467469+00:00.