I made a tool to find war reporters around the world

Hacker News

Hey HN, I've been studying abroad in the Middle East (to become a journalist) for the past few months and I've been lucky enough to meet people from all over: e.g. Sudan, Gaza, Yemen, Syria, and so on. Talking to them has deepened my worldview by a few orders of magnitude -- it's one thing to read the news, but it's another to actually talk to someone from the place you're researching. A lot of them keep up with situations in their home countries by following local reporters on social media, but they can be pretty hard to find unless you do some digging on your own. I built this to solve that problem -- in a nutshell: it's crowdsourcing frontline reporters. You can: 1. Learn about journalists/perspectives in places you might not usually see on the news 2. Add journalists that you follow (on social media, etc.) Would love any feedback! Sequoyah

Visit product View on Hacker NewsJun 24, 2025

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

80%80% 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: new · Missing: mac, agents, macos

69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

59%59% 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 · Strong signals: month · Missing: mobile apps, ios, personal

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

43%43% 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

20%20% 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.

Incorrect prediction on native model

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