21–29 of 29 posts
It assumes "a relevant (i.e. non-clickbait) link would have its text appear frequently on the actual page". Is there empirical evidence for this claim? The examples featured in the article seem mixed (some right, some wrong). It's easy enough to test: collect human judgement scores for a few hundred article links from several news sites (an afternoon's work) and compare to the algorithm.
I'm not sure that term frequency is the right way to go about the problem of clickbait. Frequently, titles and body text is meant to match up as a form of SEO. I'm not sure if this can be done through an extension, but an alternative way to go about this is by measuring time spent on the page. If the page has X words which takes Y minutes to read, but a certain number of people bounce before that time, the score is l…
It assumes "a relevant (i.e. non-clickbait) link would have its text appear frequently on the actual page". Is there empirical evidence for this claim? The examples featured in the article seem mixed (some right, some wrong). It's easy enough to test: collect human judgement scores for a few hundred article links from several news sites (an afternoon's work) and compare to the algorithm.
There is also a new version planned using a different approach.
Oh this is exactly what I wanted - I hope you make a firefox addon soon. How does your approach of looking for text frequency compared to, say, pattern-matching existing clickbait titles from a database? Can the two approaches be combined (say, by using Splice to generate a corpus, remove false positives manually, then use it to train a pattern matcher?) Not having to load the linked article has huge benefits on band…
Firefox addon is in the works. If you want to contribute code, go to github and make a pull request.
Why not train a network on ad unit headings from Outbrain and the like. That seems like it'd be pretty spot-on. These in-situ pseudo-related-articles ad units are, by their nature, click-bait. Aren't they?
So that means it's fetching the content (or at least the HTML portion) of every eligible link? That seems like potentially a lot of network traffic for what it does. Find if you have a fast connection, I suppose.
So that means it's fetching the content (or at least the HTML portion) of every eligible link? That seems like potentially a lot of network traffic for what it does. Find if you have a fast connection, I suppose.
Can be even worse. I have seen some ugly corporate services using links with GET request to perform delete operations and having serious data loss caused by crawlers like this tool.
It assumes "a relevant (i.e. non-clickbait) link would have its text appear frequently on the actual page". Is there empirical evidence for this claim? The examples featured in the article seem mixed (some right, some wrong). It's easy enough to test: collect human judgement scores for a few hundred article links from several news sites (an afternoon's work) and compare to the algorithm.