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Tag Archives: Scribnia

With new owner, Scribnia to move to Canada, New York

After a long trial separation, it looks like Scribnia and Philadelphia are breaking up.

To refresh your memory, the author rating service was founded by Dartmouth grads Russell D’Souza and Jack Groetzinger during last year’s DreamIt Ventures class. Before their time at DreamIt was up, the duo sold the company and went on to found Seatgeek, which presented at TechCrunch 50.

Scribnia was trying to become the Yelp of internet writers giving each author a page where readers could rate the writers on several criteria based on the writer’s niche. Technically Philly profiled the company last year.


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Shop Talk: Scribnia out of private alpha, releases my Scribes

A screenshot of Scribnia's MyScribes feature, to be released tomorrow.

A screenshot of Scribnia's my Scribes feature, to be released tomorrow.

The Web runs on opinion.

We Digg, Stumble, rate and recommend everything from books to blogs and, if Scribnia gets its way, you will be able to add writers to the list.

Scribnia is a University City-based Web site that allows readers to rate and recommend authors, writers and bloggers on a one to ten scale. Users can leave comments and rank authors in categories based on their writing topic. For example, a political writer can be rated as more liberal or conservative, or a tech writer can be rated on a scale of whether they write more for the general public or for tech experts.

“Readers are actually starting not to just read one-off articles on sites like Digg, but [they are] finding authors that they care about and want to come back and read,” said co-founder Russell D’Souza.

The result is a growing database of content creators that can provide users with recommendations based on previous rankings. Rate, say, baseball writer Peter Gammons high and you may be recommended other baseball writers that Peter Gammons fans rated highly. Tomorrow, the site will roll out my Scribes, an RSS reader within Scribnia that will provide author recommendations based upon the feed items the users read.


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