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Tackle Lengthy Twitter Threads with ThreadExpresso

Hacker News

Tackle Lengthy Twitter Threads with ThreadExpresso

Hey HN community, I wanted to share a Chrome extension I've been working on called ThreadExpresso. It uses ChatGPT to summarize Twitter threads, making it easier to quickly understand the key points. Features: - Time-saving Summarization: Get to the essential information in long threads without spending too much time scrolling. - Improved Twitter Experience: More easily navigate and engage with complex conversations. - Summary Length: You can choose between short summary and detailed summary. - Language Support: Works with threads in multiple languages, making content more accessible. I hope you'll give ThreadExpresso a try, and I'm looking forward to hearing your opinions and suggestions on how it can be improved!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
66%66% 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: chatgpt · Missing: mac, agents, macos
60%60% 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
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
26%26% 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 · Strong signals: chat · Missing: web3, crypto, cryptocurrency
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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