Ne

News geolocation website

Hacker News

News geolocation website

The idea: The idea is to create a news aggregator that geolocates the news, it analyses the news and displays an article on a street/city/region (location in general) if it is mentioned in that article. The website will later give you notifications about what is mentioned in the news nearby. The current situation of the project: For now I have a minimum viable product, I have the website up and running that shows how the news will be displayed on a map. What I am asking: It will be really very nice of you if you can give me feedback, any feedbacks even negative ones are really more than appreciated. I know there are many bugs, bad design, lack of content but the question I am asking you is would you use such a website/mobile app if it existed? Do you like the idea? Do you think it is worth it if I finish building such a website? Here is the link to the website: http://www.toperudite.com/ Here is the link to the newsmap: https://www.toperudite.com/pages/news/newsmap Please don't hesitate to fill the following survey (it takes less than 3 minutes) https://docs.google.com/forms/d/e/1FAIpQLSe9q_0roqwtipe4KLyR... Here is a link to a slack channel : https://join.slack.com/t/toperuditebetatesters/shared_invite... Here is a quick youtube video https://www.youtube.com/watch?v=CrwvY049ipE Thank you very much for your time :)

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Actual performance

41points
57comments
Made the leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
71%71% 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.
Hacker NewsStrong engagement from HN community · Strong signals: exist, ide, io · Missing: https docs, excited, just released
61%61% 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 HuntOn track for Day 1 leaderboard · Strong signals: slack, google, new · Missing: mac, agents, macos
53%53% 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
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: video, google · Missing: mobile apps, ios, personal
27%27% 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
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
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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