Showing posts with label social media. Show all posts
Showing posts with label social media. Show all posts

Monday, June 2, 2014

Big social platform shares - added Stumble Upon likes, shares, lists

And another script to check for social shares...this time more details around stumble upon (no, not really active there, anymore, although it has led me to a few outstanding sites).  The older version of this script pulls stumble data, but this shows pageviews from stumblers, not amplification through stumble activities. So this was mixing traffic data with engagement data - fixed now.



The data for stumble is pulled in two steps - first get the badge ID for the url, and with that pull the data (likes, shares, lists) for it. They all go into just one variable below, tab delimited, and then per echo into the larger list. That's why there are not 3 fields immediately visible when adding the data, but just seemingly one.


echo -e "Url\tripples\tFB-comments\tFB-shares\tFB-likes\ttwitter\tlinkedin\tstumble_likes\tstumble_shares\tstumble_lists" > "${1}-all-social-shares".csv
while read -r shortline ;
 do
This line is to replace special characters with their html encoding...
line=$(echo $shortline | sed -e 's/\?/\%3F/g' -e 's/&/\%26/g' -e 's/#/\%23/g')
gpull="https://plus.google.com/ripple/details?url=${line}"
ripples=$(wget -qO- "${gpull}" | grep -o "[0-9]*\s*public\s*shares.<" | sed "s/[^0-9]//g"  | tr "\n" "\t" | sed 's/\thttp/\nhttp/g'| sed 's/\t//')
commentpull="https://api.facebook.com/method/fql.query?query=select%20comment_count%20from%20link_stat%20where%20url=%22${line}%22&format=json"
comment_count=`wget -qO- $commentpull | sed -e 's/^.*://g' -e 's/\}//g' -e 's/\(]\)//g'`
echo "comment count: " $comment_count
sharepull="https://api.facebook.com/method/fql.query?query=select%20share_count%20from%20link_stat%20where%20url=%22${line}%22&format=json"
share_count=`wget -qO- $sharepull | sed -e 's/^.*://g' -e 's/\}//g' -e 's/\(]\)//g'`
echo "share count: " $share_count
likepull="https://api.facebook.com/method/fql.query?query=select%20like_count%20from%20link_stat%20where%20url=%22${line}%22&format=json"
like_count=`wget -qO- $likepull | sed -e 's/^.*://g' -e 's/\}//g' -e 's/\(]\)//g'`
echo "like count: " $like_count
twitterpull="http://urls.api.twitter.com/1/urls/count.json?url=${line}&callback=twttr.receiveCount"
twitternumber=$(wget -qO- "${twitterpull}"  | grep -o 'count\":[0-9]*\,' | sed -e 's/count//g' -e 's/,//g' -e 's/://g' -e 's/"//g' )
echo "twitter: " $twitternumber
linkedpull="http://www.linkedin.com/countserv/count/share?format=json&url=${line}" #echo ${linkedpull}
linkednumber=$(wget -qO- "${linkedpull}" | grep -o 'count\":[0-9]*\,' | sed -e 's/count//g' -e 's/,//g' -e 's/://g' -e 's/"//g' )
echo "linkedin count: " $linkednumber
stumblepull=`wget -qO- "http://www.stumbleupon.com/services/1.01/badge.getinfo?url=${line}" | grep -o "publicid.*views" | sed -e "s/publicid//" -e "s/\":\"//" -e "s/\",\"views//"`echo $stumblepullstumblenumber=$(wget -qO- "http://www.stumbleupon.com/content/${stumblepull}" | grep "mark>" | sed -e "s/^.*\">//" -e "s/<.*$//" -e "2d" -e "4d" -e "6d" | tr "\n" "\t")

echo -e "${line}\t${ripples}\t${comment_count}\t${share_count}\t${like_count}\t${twitternumber}\t${linkednumber}\t${stumblenumber}" >> "${1}-all-social-shares".csv
done < $1 
cat -A "${1}-all-social-shares".csv

Wednesday, April 23, 2014

Someone has lots of posts with the same amount of shares, comments, linkedin post - how does this happen?

One of my favorite projects right now is to check how competitors (to our Techpageone) are performing with their content - and one aspect of that is the social media engagement their content receives.

This time I looked at a different competitor, their site is targeted at their medium sized companies, if I am not mistaken.

As usual, I get a list of urls with a little script, after a bit of cleanup, the list has 5326 urls in it.
Then I run a second script to check for social shares on Google Plus, Facebook, Twitter, Stumble upon, Linkedin. Then I sort - and that's where it got really interesting, see all the duplicate numbers in FB and Linkedin? This looks very much not like an organic, natural result. (Twitter and ripples are different enough - if very low).




So, is the tool working? Let's see a sanity check, where I compare the numbers with numbers from sharetally.com. Share Tally checks a lot more (small) social media platforms, but includes all platforms my script checks, so the numbers should never be lower, and sometimes slightly higher. Works pretty well as you can see:

Is the tool stuck, cannot retrieve numbers? Sanity check no 2, this time just different urls in the same scan:



Nope, works just fine.

Manual check:
The pages do not have consistent (if any) canonical, they seem genuinely different articles from various authors, to various dates.

What, please can cause this share pattern?
These are the potential causes I can imagine (help me if you see more!)
  • Coincidence 
  • Highly disciplined workforce sharing over and over + great internal process
  • Paid sharing 
  • Automated sharing 
What am I missing? What do you think is most likely?

Thursday, March 27, 2014

Rackspace blog - ripples, likes, shares, comments


Rackspace this time in the focus. How does the Rackspace blog do in Facebook comments, likes and shares? Pretty ok, I would say, as well as they do with ripples. It is not the industry blog like moz with the public shares we can see there, but still pretty good numbers for a company blog, quite in the range of the coveted Moz guest post blog .




Again used these scripts to get Facebook data, this to get the Google ripples.

Monday, January 27, 2014

Guest blogging on Moz.com: Good location to get ripples

Last week I checked the company blog of moz.com for ripples, with truly astounding numbers. This week I decided to check on their user generated content - you find it at moz.com/ugc.

First, I pulled all urls from the sitemap moz.com/ugc-sitemap.xml , then again used the ripple script to get the number of ripples = public shares per url. Each url stands for a blog guest post. 

The results are impressive again - user generated content on 1708 posts generates 1251 ripples, with the top posts having 73 and 56 ripples.

The top post "http://moz.com/ugc/google-plus-authorship-one-critical-thing-you-need-to-know" author +Samuel Scott currently is in 222 people's circles on G+ currently, and I doubt there are many other places, if any, where he could have gotten as many shares as here (nor would I or many others, just to be clear).


Again - moz is a great place for seo content, and this narrow focus now on inbound marketing is highly beneficial for readers, for writers, and for the company.
Imagine to add 1251 ripples to YOUR site with guest blogging! 
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