Va

Valme.io, another Reddit-like alternative with monetary applause

Hacker News

Valme.io, another Reddit-like alternative with monetary applause

I developed this years ago but, given what's going on today, figured I'd resubmit for your evaluation (and perhaps find some enthusiasts interested in working on the UI and marketing). The tl/dr for why you should consider valME.io: Benefits to users/content creators: - OPs earn money for their content (karma is redeemed for Bitcoin). - Posts and comments have full long-form HTML support. - All content banned by mods is transparent (including reason) and remains visible in the graveyard community (both posts and comments). - All voting is transparent. We don't use vote fuzzing because we handle spam and vote brigades much differently. - You can create multiple levels of sub-communities with content that rolls up, making it much easier to start competing communities where your content is seen by non-subscribers. - Abandoned communities can be restarted by anyone. - No shadowbans. - There is a cost to downvote and flag which curtails trolls and downvote brigades. - Although there's a cost, users who help mods flag posts and comments earn karma rewards/bounties and can get their costs reimbursed. Benefits to mods: - valME.io values both free expression and free association and won't play the slippery slope game of selective or arbitrary ban discrimination. Communities will never be banned. Content and users will only be removed when against our ToS (i.e., illegal, threatening, violates an individual's privacy, interferes with website operations). - While mods can have different levels with different permissions, all communities have a single owner who has final decision-making authority and accountability. - Mods can customize the karma types applicable to their communities and can have multiple karma types per post/comment (which allows you to understand things like which user is contributing the most "intelligent" content from the "funniest" content, which communities have the most "agreeable" or "helpful" content, etc.). - Mods can create contests with karma rewards to encourage community building and which are based on custom-definable algorithms (e.g., number of posts, comments, upvotes, etc. within/across communities; minimum participation requirements; multiple award levels). - In addition to customizable HTML and css (which can make the community look completely different from the base template), community owners can have their own custom domain names with SSL. (A mod could use css customizations to remove all voting or just downvotes, but doing so would make some benefits useless.) - While valME.io doesn't earn any money from advertising to avoid conflicts of interest, sponsor account mods can earn 100% of the revenue from their own advertising (via Javascript). - Mods can ban users or domains for customizable timeframes or can limit the number of posts/comments allowed. - Mods can customize the algorithm used to get to their front pages (e.g., quantity of votes by karma type, quantity of views, user age, quantity of comments, post age, number of flags with which a user is shamed) or they can use reddit's standard algorithm. (valME's general front page selection criteria uses its own customized algorithm.) - Matomo Analytics is integrated, making detailed statistics available to mods. Mods can use this information (from users who don't block tracking) to do things like reward websites that help market content.

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: started, including · Missing: supports, reddit linkedin, podcasting
96%96% 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: user, single · Missing: mac, agents, macos
72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: lua, 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.
Acquire.comPre-revenue stage for this audience · Strong signals: revenue, subscribers · Missing: arr, mrr, profit
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: reward · 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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