Hey Felix @fxgr I installed to give it a try. I tried the 'Give me 5' feature on bbc.co.uk/news. It returned 5 articles all about P Diddy on the first two tries. I tried a 3rd time and got 5 articles all about a charity leader stepping down. Interested in what supposed to be returned. Is it 5 mixed articles or 5 articles about 1 topic on the page. Interesting idea and thanks for making and sharing! Edit: I've also added a 'Follow' to this page, to see what will happen!
@prattarazzi Hey Eddie! Max here, I programmed the extension. Thanks for trying it out!
It works best if you're on a single article page because it grabs the text on that page to recommend content. If you're on a page with a lot of different text content you can also highlight a paragraph, right click and send to NewsBot to get related articles for that text only.
@maxnovakovic Hey Max. Awesome. Thanks for the tips. Now I'm waiting for you to create that extension that works on product pages to find 5 related or competitive products to the product on that page :-)
@prattarazzi That's actually something that we're working on! We've got a demo online using data about public companies. Here's an early demo of it showing results for Tesla https://lateral.io/visualiser/bl... It'd be great to hear your thoughts on this!
@maxnovakovic Haha! That's handy for finding similar companies! This question applies to both NewsBot and the demo: are the related items returned in any particular order e.g. ranked most related (top) to least related (bottom), or does it not work that way?
@prattarazzi They're sorted by most relevant at the top at the moment. We're planning to add the ability to sort by date to NewsBot soon so you get the newest news at the top.
Amazing product....just sometimes suggestions are not that appropriate but still it's very good as sometimes it's must required thing! Will try it deeply and would love to give better feedback to the team. Nice work guys :)
@92akshit Thanks a lot for trying it out and the feedback! We are always looking to identify its weak spots, if you're happy to send through the articles it preformed worse on please do! If you prefer email I’m martin@lateral.io. Would also love to hear how you find using it over time!
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