RRepoGEO

REPOGEO REPORT · LITE

royal12646/Chinese-offensive-language-detect

Default branch main · commit 0c16d4fd · scanned 6/6/2026, 3:23:07 AM

GitHub: 805 stars · 53 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface royal12646/Chinese-offensive-language-detect, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    ["chinese-nlp", "offensive-language-detection", "hate-speech-detection", "content-moderation", "natural-language-processing", "text-classification", "machine-learning", "deep-learning", "data-generation", "mandarin"]
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root. For example, you could use the MIT License text, which is permissive and widely adopted, or choose another license that fits your project's goals.
  • mediumreadme#3
    Reposition the README's opening to highlight the solution

    Why:

    CURRENT
    # Chinese-offensive-language-detect
    
    **本数据集用于中文攻击性语言检测任务的研究与开发,包含大量具有攻击性、侮辱性、歧视性、涉黄等内容的文本示例。这些文本仅用于自然语言处理领域的分类建模、对抗鲁棒性测试、语言安全性研究等学术与工程目的。**
    COPY-PASTE FIX
    # Chinese-offensive-language-detect
    
    本项目旨在通过数据生成技术、模型微调技术、加权投票技术来检测以下6种有害文本:涉黄有害文本、辱骂/谐音辱骂有害文本、地域、性别、种族、职业攻击有害文本。
    
    **本数据集用于中文攻击性语言检测任务的研究与开发,包含大量具有攻击性、侮辱性、歧视性、涉黄等内容的文本示例。这些文本仅用于自然语言处理领域的分类建模、对抗鲁棒性测试、语言安全性研究等学术与工程目的。**

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface royal12646/Chinese-offensive-language-detect
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Cloud Natural Language API
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Natural Language API · recommended 2×
  2. Hugging Face Transformers · recommended 2×
  3. Baidu AI Cloud Content Moderation · recommended 1×
  4. Tencent Cloud Content Moderation · recommended 1×
  5. Alibaba Cloud Content Moderation · recommended 1×
  • CATEGORY QUERY
    How to detect and filter various types of offensive language in Chinese text?
    you: not recommended
    AI recommended (in order):
    1. Baidu AI Cloud Content Moderation
    2. Tencent Cloud Content Moderation
    3. Alibaba Cloud Content Moderation
    4. Google Cloud Natural Language API
    5. Hugging Face Transformers
    6. Python's `re` module
    7. Microsoft Azure Content Moderator

    AI recommended 7 alternatives but never named royal12646/Chinese-offensive-language-detect. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a solution to identify hate speech and discriminatory content in Mandarin.
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Natural Language API
    2. Baidu AI Cloud NLP
    3. Tencent Cloud NLP
    4. OpenAI GPT-3.5/GPT-4
    5. Hugging Face Transformers
    6. Microsoft Azure Cognitive Services - Text Analytics
    7. scikit-learn
    8. TensorFlow
    9. PyTorch

    AI recommended 9 alternatives but never named royal12646/Chinese-offensive-language-detect. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of royal12646/Chinese-offensive-language-detect?
    pass
    AI did not name royal12646/Chinese-offensive-language-detect — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts royal12646/Chinese-offensive-language-detect in production, what risks or prerequisites should they evaluate first?
    pass
    AI named royal12646/Chinese-offensive-language-detect explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo royal12646/Chinese-offensive-language-detect solve, and who is the primary audience?
    pass
    AI did not name royal12646/Chinese-offensive-language-detect — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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  • Brand-free category queries5 vs 2 in Lite
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