A website for sharing the "Good, Bad, and Why"s of urban spaces

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Hello HN! We're a small team in Kyoto building a website called dédédé ( https://dedede.de/en ) that invites people to share the various positives, negatives, oddities, etc. they find in urban spaces. The project grew out of an earlier effort where we'd built an app that assisted participatory urbanism workshops run by local nonprofits. With the new platform, we're trying to build something similar but more casual and hopefully with broader appeal, that'll be fun to use even outside of formal workshop situations. We'd love to hear your thoughts!

Visit product View on Hacker NewsMar 24, 2025

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

77%77% 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews

55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: profit · Missing: arr, mrr, revenue

17%17% 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.

Incorrect prediction on native model

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