This document summarizes a social data mining workshop presented by Dennis Yu. The workshop covered an overview of social data APIs, natural language processing techniques for determining user intent, data modeling, the Facebook Graph API and explorer tool, competitive intelligence, tying users across social networks, Facebook insights and APIs, analyzing successful Facebook posts and fans, custom audience targeting, new partner targeting options, hands-on SQL exercises for analyzing social data, the Twitter stream API, a case study on how Gordmans grew their Facebook fans cost-effectively through engaging content, geo-targeting strategies, other social APIs, analyzing LinkedIn ads data, and wrapping up the workshop.

1. Social Data Mining Workshop
Presented by
Dennis Yu: dennis@blitzmetrics.com / @dennisyu

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@dennisyu
Overview of Social Data APIs

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Natural Language, Not Keywords
to Determine Intent
Under the Hood – the Natural Language Interface of Graph Search
@dennisyu

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@dennisyu

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@dennisyu

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@dennisyu

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@dennisyu
Data Model Overview

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Graph API
http://developers.facebook.com/docs/reference/api/
@dennisyu

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@dennisyu
Facebook Graph API Explorer
http://developers.facebook.com/tools/explorer/

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@dennisyu
Competitive Intelligence

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@dennisyu
Tie users together across social networks with findByEmail

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@dennisyu
Facebook Insights
and Graph APIs

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@dennisyu

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Fuddruckers most engaging post got
over 34,000 likes and 1,100 comments!
In a community of 100,000 fans, this is outstanding.
@dennisyu

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The reason this post was so successful was that Fudds helped out a community after a tragic shooting, and a fan decided to thank them.
These types of scenarios are a perfect way to use social media to amplify the good things you do in real life.
https://www.facebook.com/fuddruckers/posts/10151137497379563
But the post wasn’t from Fuddruckers. It was from a loyal fan.
@dennisyu

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Who are Fudd’s Top Fans by Participation?
@dennisyu

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Which fans are the most influential?
@dennisyu

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Meet Heather.
Winner of Fudd’s top post.
Heather Orlowski, the fan who posted the top post, comes in 7th by number of total interactions, but she is by far the most influential.
Her influencer score is 100 times higher than the next person on that list - all thanks to her viral post.
Fans by Participation
Fans by Influence
@dennisyu

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People Talking About This (PTAT):
Total number of people who have had a brand related action show up in their news feed.
Heather’s post generated a spike in PTAT
@dennisyu

20. Let the CAT out!
Custom Audience Targeting: Match and segment, even if you don't run ads.
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@dennisyu
Super-Charge Your Sales With “Custom Audiences”

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@dennisyu
Facebook’s New Partner Targeting
Run ads based on a user’s retail shopping behavior and other offline information.
Get the numbers.

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Hands On Exercise
"SQL cheat sheet"
select f.userid, u.name, group_concat(i.name), count(i.name) as interestcount, f.pageid from fbpagefans f inner join fbuserinterests i on i.userid=f.userid inner join fbusers u on u.userid=f.userid where pageid=55715345255 group by userid
All posts for a given page (page ID is LB): select * from fbposts where ownerobjectid=70070202017 and ownerobjectid=fromid;
Count of comments on a post that contain a word: select count(*) from fbcomments where postid=168030169948013 and message like ‘skirt’; (change the postid)
Group all comments on a post by exact message select trim(message) as msg, count(*) as commentcount from fbcomments where postid=168030169948013 group by trim(message);
Fans sample size for page: select count(*) from fbpagefans f where f.pageid=70070202017;
Number of users within sample with a specific interest (exact name unless you use SQL’s “LIKE” keyword): select count(*) from fbpagefans f where f.PageID=70070202017 and exists(select * from fbuserinterests i where i.UserID=f.UserID and i.Name=‘Reading’);
Average friend count for fans of a set of pages: select avg(FriendCount) from fbpagefans f inner join fbusers u on u.UserID=f.UserID where f.PageID in(70070202017) and u.FriendCount>0;
Average friend count for commenters on a given set of pages: select avg(friendcount) from fbcomments c inner join fbusers u on u.UserID=c.FromID where c.OwnerObjectID in(70070202017) and u.FriendCount>0;
Average friend count for users who like posts on a given set of pages: select avg(friendcount) from fblikes c inner join fbusers u on u.UserID=c.FromID where c.OwnerObjectID(70070202017) and u.FriendCount>0;
Engagement as defined by # of interactions (not # of users interacting) vs # of fans set @pStart=‘2011-09-30’; set @pEnd=‘2011-10-06 23:59:59’;

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@dennisyu
Twitter Stream API

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@dennisyu

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@dennisyu

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@dennisyu

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How Gordmans got Facebook Fans for Cents.
@dennisyu
CASE STUDY

28. Highly engaged content equals positive fan growth
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@dennisyu

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@dennisyu
Geo-targeting works!

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More earned media at a cheaper rate
@dennisyu

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@dennisyu
Other APIs

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@dennisyu

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@dennisyu

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@dennisyu
Run Similar Counts Against LinkedIn’s Ads Tool

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@dennisyu
Wrapping Up

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THANK YOU
Dennis Yu
CEO of BlitzMetrics
dennis@blitzmetrics.com / @dennisyu