RRepoGEO

REPOGEO REPORT · LITE

stepthom/text_mining_resources

Default branch master · commit 31fb395f · scanned 6/7/2026, 9:03:04 AM

GitHub: 597 stars · 197 forks

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 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 stepthom/text_mining_resources, 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
  • highabout#1
    Clarify the 'About' description to specify it's a collection of external links

    Why:

    CURRENT
    Resources for learning about Text Mining and Natural Language Processing
    COPY-PASTE FIX
    A curated collection of external links and resources for learning about Text Mining and Natural Language Processing.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the text of the MIT License.
  • mediumhomepage#3
    Add the repository URL as the homepage

    Why:

    COPY-PASTE FIX
    https://github.com/stepthom/text_mining_resources

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 stepthom/text_mining_resources
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/transformers
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/transformers · recommended 2×
  2. Coursera's Deep Learning Specialization by Andrew Ng · recommended 1×
  3. fast.ai's Practical Deep Learning for Coders · recommended 1×
  4. Stanford's CS224n: Natural Language Processing with Deep Learning · recommended 1×
  5. Speech and Language Processing by Jurafsky and Martin · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive collection of resources for learning natural language processing?
    you: not recommended
    AI recommended (in order):
    1. Coursera's Deep Learning Specialization by Andrew Ng
    2. Hugging Face Transformers (huggingface/transformers)
    3. fast.ai's Practical Deep Learning for Coders
    4. Stanford's CS224n: Natural Language Processing with Deep Learning
    5. Speech and Language Processing by Jurafsky and Martin
    6. Kaggle Learn (NLP Micro-course)
    7. Google's Machine Learning Crash Course (NLP section)

    AI recommended 7 alternatives but never named stepthom/text_mining_resources. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to find reliable resources for sentiment analysis, topic modeling, and text classification?
    you: not recommended
    AI recommended (in order):
    1. scikit-learn (scikit-learn/scikit-learn)
    2. NLTK (nltk/nltk)
    3. spaCy (explosion/spaCy)
    4. Gensim (piskvorky/gensim)
    5. Hugging Face Transformers (huggingface/transformers)
    6. fastText (facebookresearch/fastText)
    7. Keras (keras-team/keras)
    8. TensorFlow (tensorflow/tensorflow)

    AI recommended 8 alternatives but never named stepthom/text_mining_resources. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    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 stepthom/text_mining_resources?
    pass
    AI named stepthom/text_mining_resources explicitly

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

  • If a team adopts stepthom/text_mining_resources in production, what risks or prerequisites should they evaluate first?
    pass
    AI named stepthom/text_mining_resources 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 stepthom/text_mining_resources solve, and who is the primary audience?
    pass
    AI did not name stepthom/text_mining_resources — 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?

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stepthom/text_mining_resources — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite