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As a Data Science Blogger Does Your Opinion Count?

Summary: If you want to make yourself heard as an author in data science, consider Google Author Rank.

OK, if you blog you are by definition concerned about two things, 1.) getting your observations out there, and 2.) seeing if anyone cares.  It’s the part about seeing if anyone cares that’s the difficulty.  Some blog platforms offer page views each time someone opens your material.  That’s a good guide.  But not all platforms offer that which leaves you with the more sophisticated and mysterious measures in the SEO world like page rank.

Now there is a new measure called “Author Rank” that promises new insight.  There’s quite a good summary article ‘A Guide to Google’s Author Rank’ by Gareth James that tells you pretty much everything you’ll need to know whether your audience is here on or anywhere else.

This new measure has its roots all the way back in a 2005 measure called Agent Rank.  Here, in part, is what Google said about Agent Rank back then:

 “The name of the writer can be used to influence the ranking of web search results by indicating the writer responsible for a particular content piece … Assuming that a given writer has a high reputational score, representing an established reputation for authoring valuable content, then additional content authored and signed by that writer will be promoted relative to unsigned content or content from less reputable writers in search results.”

In short, Author Rank is designed to identify content creators within their search results and allows Google to favor them in page rankings based on their traditional guides of frequency, links, and all the other magic stuff in that pot.

There is also an anti-plagarism aspect to this.  If you have an Author Rank enabled in your blog and you found out someone copied your content without your permission Google / DMCA will favor you as the real source and will penalize the spammer accordingly.

There’s a setup procedure to go through that starts with signing up a Google+ account.  The rest of the process is described in Gareth’s article linked above.

Once it’s setup and verified then there are strategies you can use to optimize your score much in the same manner as SEO.

So all you aspiring and current data science and big data authors, if you want to secure your place in the pantheon, this is something you’ll want to look into.

Once again, Gareth James original article is found here.

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Comment by Vincent Granville on December 16, 2015 at 8:49am

What do you think of Klout's score to rank bloggers by popularity? Last time I checked, it was very biased: your rank would be low unless you sign-up with Klout (mine miraculously spiked after signing up). However, its use is widespread among journalists.

Another issue with these scoring systems is the lack of relevancy. You can be a great data science blogger but a poor IoT blogger. How do these systems handle this? The issue is that they have very poor taxonomies, and thus do a poor job assigning someone to data science, IoT, or any other category. Some of the highest scores in data science are people totally irrelevant to data science. And some great data scientists are missing. 


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