RRepoGEO

REPOGEO REPORT · LITE

cpsievert/LDAvis

Default branch master · commit 5067f7b8 · scanned 6/15/2026, 3:59:30 PM

GitHub: 570 stars · 130 forks

AI VISIBILITY SCORE
86 /100
Healthy
Category recall
2 / 2
Avg rank #1.5 when recommended
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 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 cpsievert/LDAvis, 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
  • highhomepage#1
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    https://cran.r-project.org/web/packages/LDAvis/index.html
  • mediumreadme#2
    Clarify the repository's license in the README

    Why:

    COPY-PASTE FIX
    Add a section like 'License' to the README, stating: 'The LDAvis package is released under [Specify License(s) here, e.g., GPL-3.0 or MIT]. Please see the LICENSE file for full details.'
  • lowreadme#3
    Add a dedicated 'Examples' section to the README

    Why:

    COPY-PASTE FIX
    Add a new 'Examples' section to the README, including a direct link to the movie review example mentioned in the text and any other live demos or detailed vignettes.

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
2 / 2
100% of queries surface cpsievert/LDAvis
Avg rank
#1.5
Lower is better. #1 = top recommendation.
Share of voice
15%
Of all named tools, what % are you?
Top rival
topicmodels
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. topicmodels · recommended 1×
  2. textmineR · recommended 1×
  3. stm · recommended 1×
  4. plotly · recommended 1×
  5. shiny · recommended 1×
  • CATEGORY QUERY
    I need an R tool to interactively visualize topics from a fitted LDA model.
    you: #1
    AI recommended (in order):
    1. LDAvis ← you
    2. topicmodels
    3. textmineR
    4. stm
    5. plotly
    6. shiny
    7. tidytext
    8. ggplot2
    Show full AI answer
  • CATEGORY QUERY
    What are good web-based tools for interpreting text topic models in R?
    you: #2
    AI recommended (in order):
    1. Shiny
    2. ldavis ← you
    3. textplot
    4. topicdoc
    5. quanteda.textmodels
    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 cpsievert/LDAvis?
    pass
    AI named cpsievert/LDAvis explicitly

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

  • If a team adopts cpsievert/LDAvis in production, what risks or prerequisites should they evaluate first?
    pass
    AI named cpsievert/LDAvis 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 cpsievert/LDAvis solve, and who is the primary audience?
    pass
    AI named cpsievert/LDAvis explicitly

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

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cpsievert/LDAvis — 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