Are you creating the content your audience actually wants to consume, or are you just talking about yourself?
What sort of content will your audience read, out of the endless supply at their fingertips? Formal news articles or blog posts from your staff and readers? An event calendar updated daily, or a longread every month? Static web pages, or a deeply granular database with faceted search?
And have you figured out how to get it to them, develop engagement around it, and translate that success into something concrete, fulfilling your mission? How many of the friends and organisations in your network amplify your message regularly?
Need answers? Get in touch.
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This month sees the first generation of Hubs (other than mine) go live, so it’s time to imagine what comes next: AI integration? Filter-bubble Piercers? HubBots? Factcheck-driven credibility scores?
The Four Horsemen of this emerging Textopia are... Roam attempts to implement a near-full conception of hypertext as originally conceived by visionaries... looks like a cross between a slightly weird wiki and ... Evernote. It’s not... block-level addressability, transclusion ... and bidirectional linking ... utterly transform the writing experienc…
there are big issues with tags that limit their usefulness... tags are scattered... over 1 million unique tags. Many ... duplicates ... or so close that they have the same audience... represent each tag by a vector of numbers in a multi-dimensional vector space...find the meaning of these thousands of tags in a way that can represented by vector…
We made a fake news detector with above a 95% accuracy (on a validation set) that uses machine learning and Natural Language Processing that you can download here. In the real world, the accuracy might be lower... we decided to just try and scrape domains that were known fake, real, satire, etc. and see if we could build a data set quickly... Th…
The News Quality Scoring (NQS) will combine quality journalism content with new machine learning algorithms... as batch of stories enter the platform, they are scored on a 1-5 scale ... quality ... automatically and in real time.... Quantifiable Signals ... look at structure and patterns of the HTML page, advertising density, use of visual eleme…
News Quality Scoring Project ... humans and algorithm to separate “commodity news” from “value-added news” ... based on quantifiable and qualitative signals — like word count, freshness versus evergreen material, quote density, contextualization, and the presence of a byline... human/machine, subjective/objective hybrid as the still-under-constru…
Facebook’s application for Patent 0350675: “systems and methods to identify objectionable content.” ... filed in June 2015, describes a sophisticated system for identifying inappropriate text and images and removing them from the network... improve the detection of pornography, hate speech, and bullying... much easier to identify than false news s…
There is no shortage of content aggregators and aggregators of aggregators... give us a better overview of all the sources of information we have subscribed to and found ourselves now depending on... Constantly checking our feeds for new information, we seem to be hoping to discover something of interest, something that we can share with our ne…
"Machine learning can help by finding those hidden patterns you probably didn’t even know existed, so you can tune your marketing campaigns accordingly.... DataPop relies on semantic search and natural-language processing to infer connections between what consumers enter into the search window and what they really want, and then on machine learn…
"... envisions a Yahoo that’s as ubiquitous as computers seem destined to be. Phones, watches, public terminals, brain implants — Yahoo wants to be able to deliver content to all of them... Yahoo Labs’ biggest focus appears to be on machine learning... a dedicated machine learning group based in New York; ... “hardcore science and some theory,…
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