Tynt: What's being copied from your website right now?
1–10 of 23 posts
Re: Tynt: What's being copied from your website right now?
#2What happens if the user just deletes the link, as I have with the above quote?
Re: Tynt: What's being copied from your website right now?
#3From their about page: Tracer inserts a java script tag into the html code of your website to non-invasively track users interactions with your website content. The only change the user sees is when copied content is pasted into an email, blog or website, we automatically add a link back to the originating site at the end of the content. What happens if the user just deletes the link, as I have with the above quote?
Re: Tynt: What's being copied from your website right now?
#4Re: Tynt: What's being copied from your website right now?
#5Interesting concept, but this is not designed to find where your content has been copied onto other sites/blogs. That would be an cool service.
Re: Tynt: What's being copied from your website right now?
#6Re: Tynt: What's being copied from your website right now?
#7Re: Tynt: What's being copied from your website right now?
#8Re: Tynt: What's being copied from your website right now?
#9Re: Tynt: What's being copied from your website right now?
#10From their about page: Tracer inserts a java script tag into the html code of your website to non-invasively track users interactions with your website content. The only change the user sees is when copied content is pasted into an email, blog or website, we automatically add a link back to the originating site at the end of the content. What happens if the user just deletes the link, as I have with the above quote?
[1]After all, if someone copies your work and no once sees it, who really cares? The scope of your web crawler must be limited somehow. You could simply have it check up on your competition and/or popular links on news aggregating sites for categories related to your business. For example, if I was starting a technology blog, I could write up a Python crawler in about 30 minutes that parsed through blog articles on other popular tech blogs with related tags.