Analyze Politicians' Tweets

Hacker News

Source code here: https://github.com/pablojosecodes/CandidlyVoting Functionality demonstrated here: https://go.votecandidly.com/ Hey HN! I've been wondering for a while how we might be able to make the process of evaluating the politicians we vote for more transparent. In the most recent SF election- for example- I only really had a few promotional websites and some loose policy statements to go off of. This seems quite inefficient, especially considering how much signal- social media posts, policy decisions, interviews- exists on the internet for each politician. So, I put together Candidly ( https://votecandidly.com/ ) as an experiment (for now, it only has information on the candidates for SF's upcoming state senate election.) *The Core Idea*: Candidly indexes each politician's most recent tweets, interviews, and policy decisions- and lets you interface in a conversational manner with each politician's stated and demonstrated opinions. Repost of my previous "Show HN" because I accidentally posted the wrong repo which curtailed engagement. Believe this is in line with the HN rules. Let me know what you think!

Visit product View on Hacker NewsApr 18, 2024

Share card

Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

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

75%75% 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 HuntUnlikely to reach the leaderboard · Strong signals: code · Missing: mac, agents, macos

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

Hacker NewsMay not resonate with HN audience · Strong signals: exist, lua, ide · 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.

AppSumoMay struggle as an AppSumo deal · Strong signals: interface, efficient · Missing: plus, platform, intuitive

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

33%33% 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

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.

Correct prediction on native model

Similar products

Framed Tweets37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Framed Tweets

Hacker News2

Hurricane Tweets37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Hurricane Tweets

Hacker News56

Beyond Tweets37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Beyond Tweets

Hacker News1

Sex Your Tweets (Bayesian classifier)37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Sex Your Tweets (Bayesian classifier)

Hacker News1

Find Haiku in Your Tweets37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find Haiku in Your Tweets

Hacker News1

Lonely Tweets :'(42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Lonely Tweets :'(

Hacker News1

#e is for Ephemeral – timed deletion of your tweets55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

#e is for Ephemeral – timed deletion of your tweets

Hacker News1

Starling - geographically analyze millions of tweets45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Starling - geographically analyze millions of tweets

Hacker News11

A game made out of tweets36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A game made out of tweets

Hacker News2

Automate Your Tweets41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Automate Your Tweets

Hacker News1

Browse all products Analyze your launch