To

Tongue-in-cheek project to explore community voting using meme altcoins

Hacker News

Tongue-in-cheek project to explore community voting using meme altcoins

Meme altcoins are pretty ridiculous, and I couldn't help but notice the storm-in-a-teacup that was the Coinye West launch (currency symbol COYE, a parody altcoin named after Kanye West). I'm not sure if there is a better time to learn about hacking on altcoin daemons! Bitcoind and its forks expose a JSON-RPC server enabling API wallet management and account balance calculations. My vision was to allow Coinye miners to vote for their favourite Kanye West songs by sending coins to specific Coinye addresses. I hacked up a small Python script to create a Coinye address for each of Kayne West's music tracks and to generate a static web page listing the current voting scores. Source at: https://github.com/brotchie/coinyesbest https://github.com/brotchie/coinyesbest/tree/doge Resulting static page at: http://coinyesbest.com/ My primary findings after wasting time on this: There is a gap in open source tools to parse altcoin block chains and calculate the current balance of any given address.

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Indie HackersFits the IH revenue-focused audience · Strong signals: songs · Missing: supports, reddit linkedin, podcasting
56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: open source, io · Missing: https docs, excited, just released
40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: using, open · Missing: mac, agents, macos
36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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