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Copyright © 2015 KNIME.com AG
Customer Intelligence on Social Media
Rosaria Silipo
KNIME.com AG
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Copyright © 2014 KNIME.com AG 2
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Copyright © 2014 KNIME.com AG 3
The KNIME Platform: Open for Innovation
Powerful: Legacy Future Tools
Collaborative: Scientists Analysts
Integrative: Legacy Future Data
Transparent: Existing Future Expertise
Agile: Internal External Wisdom
3
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Copyright © 2014 KNIME.com AG 4
The KNIME Analytics Platform
4
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Copyright © 2014 KNIME.com AG 5
StatisticsData MiningMachine LearningWeb AnalyticsText MiningNetwork AnalysisSocial Media AnalysisWEKARJFreeChartCommunity / 3rd
MySQL, Oracle, etc.SAS, SPSS, etc.Excel, Flat, etc.Hive etc.XML, PMMLText, Doc, ImageWeb CrawlersIndustry SpecificCommunity / 3rd
ETLRow, ColumnMatrixText, ImageTime SeriesJavaPythonCommunity / 3rd
via BIRTPMMLXMLDatabasesExcel, Flat, etc.Hive etc.SparkText, Doc, ImageIndustry SpecificCommunity / 3rd
Over 1000 native and embedded nodes included:
5
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Copyright © 2014 KNIME.com AG 11
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The Problem
A major European Telco
12
• Can you tell us what people say about our new product?
• Can you tell us who is supporting the product and who trashing it?
• Of those, can you tell us who is an influencer?
Its Forum Site
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The Data
13
• The Data Set unfortunately cannot be shared
• Slashdot Forum Data are!
• Slashdot was a public forum built in 1997 and hosting a number of discussions: from software to philosophy, from science fiction to politics.
• Politics was the biggest discussion group
• So, politics is what we analyzed to find out:– What users were thinking about a political issue
– Who was pro and who was con
– Who was an influencer
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The Politics Group in the Slashdot DataSet
15
• 24 000 non anonymous users
• 496 posts
• 140 000 comments
• Most posts have around 200 comments
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Copyright © 2014 KNIME.com AG 16
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Text Analytics: Options
• Tag (Word) Clouds
• Topic Detection
• Topic Shift
• Sentiment Analysis
I find PRODUCT X to be very good and useful,but it is a bit too expensive.
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Text Analytics: WorkflowDocument type
is required
Loading MPQA Stanford dictionary for
sentiment attribute
Sum
of
freq
uen
cies
o
f p
osi
tive
an
d
neg
ativ
e w
ord
s p
er
po
st/c
om
men
t
Sum
of
Sum
of
freq
uen
cies
of
po
siti
ve
and
neg
ativ
e w
ord
s p
er
use
r
Scatter Plo
ts an
d Tag C
lou
ds
Rea
d D
ata
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Copyright © 2014 KNIME.com AG 19
Text Analytics: Results
Most negative user pNutz
Most positive and most
talkative user dada21
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Text Analytics: Open Questions
20
• Is dada21 an influencer?
• Is pNutz an influencer?
• Shall we take marketing actions about any of them?
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Copyright © 2014 KNIME.com AG 21
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Network Mining: Options
• User Interaction Graph
• Influencers vs. Followers
• User Network Investigation
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Copyright © 2014 KNIME.com AG 23
Network Mining: Workflow
Read Data
Create Empty Network
Create Network Content
Extract largest
sub-graph
Centrality Index for authority score
Scatter Plots
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Copyright © 2014 KNIME.com AG 24
Network Mining: Results
Dada21
Carl Bialik from the WSJ
Doc Ruby
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Network Mining: Open Questions
25
• Is Carl Bialik from WSJ positive or negative about the topic?
• Is dada21 positive or negative about the topic?
• What shall we do marketing-wise with non-influencers such as doc Ruby?
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Text Analytics and Network Mining: Workflow
Read Data
Network Mining
Sentiment Analysis
Joiner
Scatter Plots
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Copyright © 2014 KNIME.com AG 28
Text Analytics and Network Mining: Results
pNutz
Carl Bialik
dada21
Doc Ruby
99BottlesOfBeerInMyF
WebHosting Guy
Tube Steak
Catbeller
from the WSJ
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Text Analytics and Network Mining: Results
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Conclusions
31
• Is Carl Bialik from WSJ is an influencer and … neutral.
• Most influencers are actually neutral.
• Worth it keep informed
• dada21 is talking positively about each topic. Worth it to pamper him/her.
• Of the negative talking users, pNutz though obnoxious, is not the main worry. Catbeller is.
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Copyright © 2014 KNIME.com AG 32
Where can I find all this?
White paper, Workflows, and Data is available on the KNIME web site:
http://www.knime.com/white-papers (section Social Media)
https://www.knime.org/files/knime_social_media_white_paper.pdf
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Copyright © 2014 KNIME.com AG 33
Resources
• KNIME (www.knime.org)• BLOG for news, tips and tricks(www.knime.org/blog)
• FORUM for questions and answers (tech.knime.org/forum)
• EXAMPLE SERVER for example workflows
• LEARNING HUB (www.knime.org/learning-hub)
• KNIME TV channel on
• KNIME on @KNIME
• KNIME on
https://www.facebook.com/KNIMEanalytics
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Thank You
Free Copy of KNIME Beginner’s Luck Book at KNIME Press https://www.knime.org/knimepress
Promotion Code:
Barcelona2016