My first serious project, a Twitter client for Windows Phone

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I've been working the last months on a Twitter app for Windows Phone called Ocell. It all started as a test project to explore development in that platform, but I started to give it more time and released it to the Marketplace. It's my first serious project and I would like to know what does HN think about it. It's also opensourced, so you can also take a look at the code on GitHub (https://github.com/gjulianm/Ocell). It would be really great to have your feedback on this :) Thanks a lot! Windows Phone Store link: http://www.windowsphone.com/s?appid=2ca75e0f-69a4-42e9-b788-dedc31afb82a

Visit product View on Hacker NewsAug 24, 2012

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

61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

58%58% 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 · Strong signals: started · 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 · Strong signals: platform · Missing: plus, intuitive, reviews

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

25%25% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

13%13% 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.

Correct prediction on native model

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