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I Parsed Every Name from SSA Cards and Visualized the Data

Hacker News

I Parsed Every Name from SSA Cards and Visualized the Data

Hi HN! I’m Aram, a fourteen year old in Seattle. I recently found out that the social security administration (SSA) provides datasets of every name on a social security card (1880-2023)! So i made a tool for people to graph them, compare them with other names, view the most popular names of years, and even see how many people are alive with a name (using a rough actuary db also from the ssa). I would love to hear y’all’s thoughts! It's also open source https://github.com/aramshiva/nomen if you want to check out the code

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4points
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Did not reach leaderboard

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Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released
68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: visualize · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: visual, using, code · Missing: mac, agents, macos
38%38% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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