Alternatives
Products that do what Douyin Analytics Scraper does
Export Douyin hot search trends to a dataset
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Hey HN! I built TopicRadar to solve a problem I had with staying on top of what's trending in AI/ML without checking 7+ sites daily. https://apify.com/mick-johnson/topic-radar What it does: - Aggregates from HackerNews, GitHub, arXiv, StackOverflow, Lobste.rs, Papers with Code, and Semantic Scholar - One-click presets: "Trending: AI & ML", "Trending: Startups", "Trending: Developer Tools" - Or track custom topics (e.g., "rust async", "transformer models") - Gets 150-175 results in under 5 minutes Built for the Apify $1M Challenge. It's free to try – just hit "Try for…
Jan 2026 · apify.com
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2023 · v01.io
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Free tool to explore search trends by industry, niche, topic
2020
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I built this tool to help me find interesting discussions on Hacker News. I love reading HN discussions almost more than the articles themselves. However, I found that full text search, although highly performant, is not always good at surfacing interesting discussions on a certain topic -- especially if you don't know what to search for exactly. I built this by scraping the most recent ~6 million posts (that's about 2 years of history) and putting the resulting posts and their vector embeddings into Postgres. Let me know what could be improved, and if you'd like a more detailed writeup of…
2024 · searchhacker.news
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Made this todo list + calendar heat map over a couple of weekends, so its rough, but should be valuable enough to be used. Currently stores data in local storage, but I'm working on persisting data with auth + a database. Features coming in the couple weeks: (1) Search, (2) Categories. Hope you find it useful!
2023 · todogrids.com
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We built a search engine that shows you the most engaging stories/topics being shared across Twitter, Facebook, Linkedin, and Google+. We crawled over 15 million articles the past 3 months, retrieved the total number of Facebook likes, tweets, Google+’s etc and built a search index around it. Here's what our infrastructure looks like: Rails/Redis: We use the Sidekiq gem as a message queue. We have hundreds of workers that do the crawling, data mining, and number crunching. ElasticSearch: We built the search index using ElasticSearch, with the data imported from our Postgres…
2013 · buzzsumo.com
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