Dylan Greene dot com

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Automatic Bull-Sh*t detector extension for email, blogs, and browsers

March 3, 2006 4:55 PM

A friend sent me a story that was mostly true, but some details were changed. I found this out through the urban-legend-busting site Snopes.com.

We've all seen a blog entires about stories that seemed real enough but were actually urban myths, totally made up, or originally posted on parody news sites.

Here's my idea: A tool that automatically looks up content on resources like Snopes.com and lets users know when something they are about to email, post, or share is not real. It would work behind the scenes, the same way anti-phishing and anti-virus software.

A tool like this would help make all of us smarter by reducing the amount of fake information clutter we run into every day.

I already have an idea for version 2: political spin detector. Of course there have to be several different editions of that one depending on which resources our users trust for their information.

Comments

Good Idea, hard to implement, but would help alot.  Could even be extended for copyrights, as in would google a phrase, and see what turns up.

I like.

I just had the idea of a spin detector also, and found this blog entry as I just stated to research the idea.  I have a more objective idea of how it might be done though and a more general implementation.

It would automatically asses all the online media outlets in the country (why not the world!) to give them a rating on how disparaging or positive they are when dealing with certain people (eg political candidates).

Such an algorithm is concievable - you would first of all need to gather or generate a database of articles that are about people and purposefully ensure that they either treat the person positively or negatively.

Then you would have a number of people confirm this by reading and labelling each one.

Then you would talk to media experts and determine which features are particularly important or worth looking for, for example, the placement of the person at the beginning or the end, the use of nicknames, subjective comments etc.

Then you simply obtain values for each of these attributes and correlate them to the judgements of each article in the database.  If this doesn't work, you might need to employ an artificial neural net to detect features that  people didn't think of.

May or may not work, but if it did, that would finally be a way of holding the barstards accountable or at least objectively showing people how biased the media has become, particularly in Australia and the US.
 

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I liked the idea described here. Also liked Snopes.com.

good

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