Gocial – Small PoC for social media interactions

Hacker News

𝗴𝗼𝗰𝗶𝗮𝗹 More than a year ago I started working on a side project born out of the frustration I had with buffer, ifttt and zapier. The use case was pretty simple: I just wanted to share an article and some comments about it on multiple social media platforms from a single location. All sharing services had great functionalities (e.g. automated workflows) but you're always limited in the number of shares you can distribute withing a time frame without paying for premium. At the same time they all lacked support for LinkedIn which then sparked the idea for gocial. After having a look at the LinkedIn Post API I decided I’ll implement my own service in Golang and learn more about OAuth, JWT tokens and especially frontend. Here are some specs: • Golang as core language • echo framework for the HTTP and REST API part • JWT tokens for stateless authentication • deployed as AWS Lambda function via netlify • TailwindCSS, Alpine.js and simple Golang HTML templates for the frontend • more or less hexagonal architecture • currently one big monolith (ca. 14Mb binary) running in a serverless environment Read the blog post https://blog.dornea.nu/2022/12/15/releasing-gocial/ Or test it by yourself : https://gocial.netlify.app

Visit product View on Hacker NewsDec 15, 2022

Share card

Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

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

87%87% 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: single · Missing: mac, agents, macos

56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

43%43% predicted probability of success on TrustMRR, 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

42%42% 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: platform · Missing: plus, intuitive, reviews

27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

21%21% 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

PoGoSo31%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Rewiring social interactions for the 21st century.

Product Hunt+26

Your Social Media Fingerprint (maybe NSFW)39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Your Social Media Fingerprint (maybe NSFW)

Hacker News911

FAQ Off – Mitigate Mob Harassment on Social Media34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

FAQ Off – Mitigate Mob Harassment on Social Media

Hacker News1

Social Media Defaults for Mindfulness32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Social Media Defaults for Mindfulness

Hacker News1

Combat social media addiciton with foreign wikipedias38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Combat social media addiciton with foreign wikipedias

Hacker News1

Vers – Social Media as It Should Be32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Vers – Social Media as It Should Be

Hacker News1

This is what social media could be41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

This is what social media could be

Hacker News123

Unbundling Microlearning from Social Media26%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Unbundling Microlearning from Social Media

Hacker News2

Publer34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Your Social Media Superhero

Indie Hackers33$400,000/mob2b

Mizo49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Social Media Handled

Product Hunt+1

Browse all products Analyze your launch