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Title  Area  
The Social Relationship Intelligence Platform
#FBdata
Insightpool x Datasift Webinar
FACEBOOK TOPIC DATA
Meets the Power of
INSIGHTPOOL
#TopicData
Devon Wijesinghe
CEO of Insightpool
@DevonWijesinghe
Speaker
Co-founded Insightpool in
2012, and has led the
company from two to 60+
employees, acquired a Silicon
Valley start-up, Next
Principles, and is currently
revolutionizing marketing and
sales across social. 
#TopicData
Tim Barker
CPO at Datasift
@timbarker
Speaker
Joined DataSift after serving as
VP EMEA Marketing
atSalesforce, leading a world-
class marketing team to create
the social enterprise and cloud-
computing industries. Tim has
entrepreneur DNA, having
founded 3 successful startups.
#TopicData
Facebook Topic Data #TopicData
#TopicData
What data are we analysing
Facebook Page
Topic Data
Posts, Likes and Comments
on brand-owned page globally
Posts, Likes and
Comments on Facebook
#TopicData
What’s on your mind?
Content and Behaviours
7
CONTENT DEMOGRAPHICS LIKES and SHARES
Anonymized and aggregate topic data
•  Posts
•  Pages Posts
Plus engagement data
•  Likes on Posts
•  Shares on Posts
•  Comments (no text) on Posts
Data enriched with
•  Demographics
•  Topics
•  Sentiment
#TopicData
Topic/Entity Data from the Facebook Open Graph
8
Entity/Topic Detection is applied to every post
Leverages Facebook’s massive Open Graph data set to identify
topics and events. The same technology is used to surface
Public Trends on Facebook.
Enable exploration of topics related to a brand
Topics enable exploration of the data without access to raw
posts. For example - cluster the topics related to a product or
event.
Topics can be used within filters to remove noise.
Create a CSDL filter for posts for the movie “The Interview”.
fb.topics.category == “Movie" and
fb.topics.name contains “The Interview"
CONTENT
TOPICS
Sony (Organization)
The Interview (Movie)
Kudos to Sony for distributing The Interview
#TopicData
Demographics and Engagement
9
Gender
 Age Range
 Location
Male
Female
18-24
25-34
35-44
45-54
55-64
65+
Country
State / Region
Self-declared, not
derived.
Enables exploration of audience segments
Demographics for every post, comment and like.
Understand the audience engaging with your brand.
#TopicData
Privacy-First Data Management Controls
Social data never leaves Facebook
Social data is processed by DataSift technology running inside
Facebook’s network.
User identity is removed before processing
User identity is removed from social data before processing by
DataSift technology.
Results provided in aggregate, anonymized
Only summary results containing insights from 100 or more
people are delivered by DataSift.
30-day retention period for underlying social data
Data deleted from DataSift’s technology after 30 days.
Prevents analysis of minors
Minimum age applies for data collected for analysis.
#TopicData
Facebook Topic Data is a Killer App for Research
38M people in
UK, 210M
people in North
America
Share with
friends
Gender, Age,
Location,
Education,
Relationship
Status
Data
Structured for
Standardized
Analysis
Representativity Lack of demographics Unstructured dataSelf-promotion bias
#TopicData
How it Works
12
DataSift platform connects to the real-time feed
of Posts, Comments, Likes.
2 • CATEGORIZE
Filtered data can be
classified with
customer-specific
rules.
4 • QUERY
The Index is sub-
queried and
further processed
using CSDL
against 60+
attributes.
5 • ANALYTICS
Aggregated and anonymized
data returned for developers
to create applications,
analysis and visualizations.
Each customer
defines their
specific filter
based on their
criteria.
1 • FILTER
Filtered and
categorized data is
indexed into a real-
time analysis
engine.
3 • INDEX 6 • MINING AND VISUALISATION
The data is then mined and visualised
by using a range filters, classifiers
and interactive visualisations to help
you craft insights.
#TopicData
Why PYLON for Facebook Topic Data?
Data science via PYLON
for Facebook topic data is
at the center. Information
fuels Insightpool’s
targeting, messaging, and
activation flow.
#TopicData
Client Objective
Major auto parts retailer is interested in partnering with NASCAR.
Major auto parts retailer needs to find out what makes NASCAR fans tick
-Who are they?
-What topics spark influencer engagement?
Insightpool creates a PYLON for Facebook topic data filter to find Facebook
posts relevant to NASCARFILTER
Include
Tags of “NHRA, NASCAR, Motocross, drag racing, top fuel, funny car,
PEAK racing”
And NOT
Tags of “racing, race driver, ski, bicycle, professional, pro, BMX, obstacle,
spartan, champion, champ, bike, raced”
#TopicData
Data Analysis
Peak: Wednesday, August 26
All sharing and engaging on Facebook is uncovered when a filter is applied.
We discovered a peak and further investigated.
#TopicData
Deeper Dive
We focused in on the specific peak to uncover topics/
demographics that sparked increase in social sharing
and engagement.
PYLON can bring detailed breakdowns on:
Sentiment
Post’s author’s
region
Age
Country of Origin
Top Link Shared
Gender
Language
Hashtags
Media Type (Posts/Links)
Facebook Type (Comments,
Likes, Stories,)
Topics
#TopicData
Topics and Data Analysis
A multitude of anonymised and aggregated data can be drawn out from the
overall NASCAR discussion, or from any specific demographic or tag.
PYLON has the capability to create customizable tags to further filter the sharing and
engagement around NASCAR based off of phrasing, tone and sentiment.
For example, PYLON can filter out only the negative sentiment posts, to compare to the positive
sentiment posts. We can then determine the topics that are frequent in positive posts as well as
negative posts.
#TopicData
Sentiment Example
Positive Sentiment
Negative Sentiment
Tag.sentiment of fb content contains any: “love, obsessed, can’t wait,
excited, pumped, awesome, great, amazing, excitement, exciting”
Tag.sentiment of fb content contains any: “hate, stupid, dumb, don’t like,
lame, bad”
Sentiment of the overall filter Negative sentiment of towards a specific topic
#TopicData
More Insights
With PYLON for Facebook topic data,
you can visualize:
Post author’s region
Post’s author’s gender
Post author’s gender
#TopicData
Key Insights
Top 3 links shared
•  The top 3 links being shared revolving
the topic of NASCAR are all on
FoxSports URLs.
•  This can be used to inform ad buys, or
content to be pushed by the brand
Takeaway: The most amount of sharing and engagement
was coming from Fox Sports around a tribute to a driver.
#TopicData
Conclusion
•  This information informs major
auto parts retailer to be
empathetic towards NASCAR
fans and also create more
sharing and engagement around
tribute content.
•  This also informs them to place
media buys on Fox Sports where
a large percentage of traffic is
coming from.
http://foxs.pt/1NAb2pX
#TopicData
PYLON Benefits
The major auto parts retailer can now
amplify it’s targeting, messaging, and
activations around the tribute story.
Valuable Hidden Insight: The top traffic
drivers were coming from Fox Sports and
the content was a tribute to a specific driver.
Client also knows where to spend media
dollars and put their brand in front of the Fox
Sports audience to drive greater
conversions
#TopicData
#TopicData
Facebook is the foundation.
Q & A
#TopicData
Title  Area  
Thank
You!
#TopicData

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Facebook Topic Data Meets the Power of Insightpool

  • 1. Title  Area   The Social Relationship Intelligence Platform #FBdata Insightpool x Datasift Webinar FACEBOOK TOPIC DATA Meets the Power of INSIGHTPOOL #TopicData
  • 2. Devon Wijesinghe CEO of Insightpool @DevonWijesinghe Speaker Co-founded Insightpool in 2012, and has led the company from two to 60+ employees, acquired a Silicon Valley start-up, Next Principles, and is currently revolutionizing marketing and sales across social.  #TopicData
  • 3. Tim Barker CPO at Datasift @timbarker Speaker Joined DataSift after serving as VP EMEA Marketing atSalesforce, leading a world- class marketing team to create the social enterprise and cloud- computing industries. Tim has entrepreneur DNA, having founded 3 successful startups. #TopicData
  • 4. Facebook Topic Data #TopicData
  • 6. What data are we analysing Facebook Page Topic Data Posts, Likes and Comments on brand-owned page globally Posts, Likes and Comments on Facebook #TopicData
  • 7. What’s on your mind? Content and Behaviours 7 CONTENT DEMOGRAPHICS LIKES and SHARES Anonymized and aggregate topic data •  Posts •  Pages Posts Plus engagement data •  Likes on Posts •  Shares on Posts •  Comments (no text) on Posts Data enriched with •  Demographics •  Topics •  Sentiment #TopicData
  • 8. Topic/Entity Data from the Facebook Open Graph 8 Entity/Topic Detection is applied to every post Leverages Facebook’s massive Open Graph data set to identify topics and events. The same technology is used to surface Public Trends on Facebook. Enable exploration of topics related to a brand Topics enable exploration of the data without access to raw posts. For example - cluster the topics related to a product or event. Topics can be used within filters to remove noise. Create a CSDL filter for posts for the movie “The Interview”. fb.topics.category == “Movie" and fb.topics.name contains “The Interview" CONTENT TOPICS Sony (Organization) The Interview (Movie) Kudos to Sony for distributing The Interview #TopicData
  • 9. Demographics and Engagement 9 Gender Age Range Location Male Female 18-24 25-34 35-44 45-54 55-64 65+ Country State / Region Self-declared, not derived. Enables exploration of audience segments Demographics for every post, comment and like. Understand the audience engaging with your brand. #TopicData
  • 10. Privacy-First Data Management Controls Social data never leaves Facebook Social data is processed by DataSift technology running inside Facebook’s network. User identity is removed before processing User identity is removed from social data before processing by DataSift technology. Results provided in aggregate, anonymized Only summary results containing insights from 100 or more people are delivered by DataSift. 30-day retention period for underlying social data Data deleted from DataSift’s technology after 30 days. Prevents analysis of minors Minimum age applies for data collected for analysis. #TopicData
  • 11. Facebook Topic Data is a Killer App for Research 38M people in UK, 210M people in North America Share with friends Gender, Age, Location, Education, Relationship Status Data Structured for Standardized Analysis Representativity Lack of demographics Unstructured dataSelf-promotion bias #TopicData
  • 12. How it Works 12 DataSift platform connects to the real-time feed of Posts, Comments, Likes. 2 • CATEGORIZE Filtered data can be classified with customer-specific rules. 4 • QUERY The Index is sub- queried and further processed using CSDL against 60+ attributes. 5 • ANALYTICS Aggregated and anonymized data returned for developers to create applications, analysis and visualizations. Each customer defines their specific filter based on their criteria. 1 • FILTER Filtered and categorized data is indexed into a real- time analysis engine. 3 • INDEX 6 • MINING AND VISUALISATION The data is then mined and visualised by using a range filters, classifiers and interactive visualisations to help you craft insights. #TopicData
  • 13. Why PYLON for Facebook Topic Data? Data science via PYLON for Facebook topic data is at the center. Information fuels Insightpool’s targeting, messaging, and activation flow. #TopicData
  • 14. Client Objective Major auto parts retailer is interested in partnering with NASCAR. Major auto parts retailer needs to find out what makes NASCAR fans tick -Who are they? -What topics spark influencer engagement? Insightpool creates a PYLON for Facebook topic data filter to find Facebook posts relevant to NASCARFILTER Include Tags of “NHRA, NASCAR, Motocross, drag racing, top fuel, funny car, PEAK racing” And NOT Tags of “racing, race driver, ski, bicycle, professional, pro, BMX, obstacle, spartan, champion, champ, bike, raced” #TopicData
  • 15. Data Analysis Peak: Wednesday, August 26 All sharing and engaging on Facebook is uncovered when a filter is applied. We discovered a peak and further investigated. #TopicData
  • 16. Deeper Dive We focused in on the specific peak to uncover topics/ demographics that sparked increase in social sharing and engagement. PYLON can bring detailed breakdowns on: Sentiment Post’s author’s region Age Country of Origin Top Link Shared Gender Language Hashtags Media Type (Posts/Links) Facebook Type (Comments, Likes, Stories,) Topics #TopicData
  • 17. Topics and Data Analysis A multitude of anonymised and aggregated data can be drawn out from the overall NASCAR discussion, or from any specific demographic or tag. PYLON has the capability to create customizable tags to further filter the sharing and engagement around NASCAR based off of phrasing, tone and sentiment. For example, PYLON can filter out only the negative sentiment posts, to compare to the positive sentiment posts. We can then determine the topics that are frequent in positive posts as well as negative posts. #TopicData
  • 18. Sentiment Example Positive Sentiment Negative Sentiment Tag.sentiment of fb content contains any: “love, obsessed, can’t wait, excited, pumped, awesome, great, amazing, excitement, exciting” Tag.sentiment of fb content contains any: “hate, stupid, dumb, don’t like, lame, bad” Sentiment of the overall filter Negative sentiment of towards a specific topic #TopicData
  • 19. More Insights With PYLON for Facebook topic data, you can visualize: Post author’s region Post’s author’s gender Post author’s gender #TopicData
  • 20. Key Insights Top 3 links shared •  The top 3 links being shared revolving the topic of NASCAR are all on FoxSports URLs. •  This can be used to inform ad buys, or content to be pushed by the brand Takeaway: The most amount of sharing and engagement was coming from Fox Sports around a tribute to a driver. #TopicData
  • 21. Conclusion •  This information informs major auto parts retailer to be empathetic towards NASCAR fans and also create more sharing and engagement around tribute content. •  This also informs them to place media buys on Fox Sports where a large percentage of traffic is coming from. http://foxs.pt/1NAb2pX #TopicData
  • 22. PYLON Benefits The major auto parts retailer can now amplify it’s targeting, messaging, and activations around the tribute story. Valuable Hidden Insight: The top traffic drivers were coming from Fox Sports and the content was a tribute to a specific driver. Client also knows where to spend media dollars and put their brand in front of the Fox Sports audience to drive greater conversions #TopicData