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I quite wouldn't say # of items be the right approach, but rather 'average customer rating' as a combination of # of items would be useful. Mere item-count is easily inflatable by publishers/eCommerce to get its ranking up.

My 2 cents.

I support with Yusuf's answer.

It picks the count of mentions in the specific URL (homepage), rather than cumulating everything under the domain. I guess, MOZ needs to work on that to get a good match with our actual mentions from our internal reports.

I would say, Try: WebSEO, in addition to MOZ data.

MOZ does a good job on the first half list of items you mentioned.

In my part of the world, this is what I do first. On top of these data, I do my web-scraping and scripting to see what's trending in terms of social keywords. No offence, MOZ team, but we have to do this due to our very specific focus in Canadian market and domain authority tracking.

| URL: | http://www.theweathernetwork.com |
| TOTAL TWITTER TWEETS: | 2522 |
| FACEBOOK MENTIONS: | 8872 |
| GOOGLE BLOG SEARCH RESULTS: | 0 |
| DELICIOUS: | 251 |
| DIGG: |  - |
| STUMBLEUPON: | 539 |

I quite wouldn't say # of items be the right approach, but rather 'average customer rating' as a combination of # of items would be useful. Mere item-count is easily inflatable by publishers/eCommerce to get its ranking up.

My 2 cents.

I support with Yusuf's answer.

It picks the count of mentions in the specific URL (homepage), rather than cumulating everything under the domain. I guess, MOZ needs to work on that to get a good match with our actual mentions from our internal reports.