Knime customer intelligence on social edia

Copyright © 2015 KNIME.com AG
Customer Intelligence on Social
Media
Rosaria Silipo
KNIME.com AG

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

KNIME Analytics Platform
4

NODES perform tasks on data
Nodes are combined to create
WORKFLOWS
Status
Visual KNIME Workflows
Inputs Outputs
Not Configured
Idle
Executed
Error

Statistics
Data Mining
Machine Learning
Web Analytics
Text Mining
Network Analysis
Social Media Analysis
WEKA
R
Community / 3rd
MySQL, Oracle, etc.
SAS, SPSS, etc.
Excel, Flat, etc.
Hive etc.
XML, PMML
Text, Doc, Image
Web Crawlers
Industry Specific
Community / 3rd
ETL
Row,
Column
Matrix
Text, Image
Time Series
Java
Python
Community / 3rd
Includes over 1000 native and embedded nodes
via BIRT
PMML
XML
Databases
Excel, Flat, etc.
Hive etc.
Text, Doc, Image
Industry Specific
Community / 3rd
6

Who’s Using KNIME?
> 2,000,000 Downloads annually (in 2015)
> 70,000 Individuals using KNIME
> 5,000 Organizations using KNIME
> 700 Customers paying for KNIME
7

Top in User Satisfaction
2012 & 2013 Rexer Analytics Survey
Users who know KNIME love it!
8
Open Source
Overall

KNIME Analytics Platform: Try it Now!
1. Download from
www.knime.com
2. Browse the KNIME
Learning Hub at
www.knime.com/learning-hub
3. Check out KNIME Press
“KNIME Beginner’s Guide”
4. Become active on our Forum!

The Problem
A major European Telco
11
• 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

The Data
12
• 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

The Politics Group in the Slashdot DataSet
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• 24 000 non anonymous users
• 496 posts
• 140 000 comments
• Most posts have around 200 comments

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.

Text Analytics: Workflow
Document type
is required
Loading MPQA
Stanford dictionary for
sentiment attribute
Sumoffrequencies
ofpositiveand
negativewordsper
post/comment
SumofSumof
frequenciesofpositive
andnegativewordsper
user
ScatterPlots
andTagClouds
ReadData

Text Analytics: Results
Most negative
user pNutz
Most positive
and most
talkative user
dada21

Text Analytics: Open Questions
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• Is dada21 an influencer?
• Is pNutz an influencer?
• Shall we take marketing actions about any of
them?

Network Mining: Options
• User Interaction Graph
• Influencers vs. Followers
• User Network Investigation

Network Mining: Workflow
Read Data
Create Empty
Network
Create
Network
Content
Extract
largest
sub-graph
Centrality Index for
authority score
Scatter Plots

Network Mining: Results
Dada21
Carl Bialik from the WSJ
Doc Ruby

Network Mining: Open Questions
24
• 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?

Text Analytics and Network Mining: Workflow
Read Data
Network Mining
Sentiment Analysis
Joiner
Scatter Plots

Text Analytics and Network Mining: Results
pNutz
Carl Bialik
dada21
Doc Ruby
99BottlesOfBeerInMyF
WebHosting Guy
Tube Steak
Catbeller
from the WSJ

Text Analytics and Network Mining: Results

Conclusions
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• 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.

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_whit
e_paper.pdf

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
32

Thank You
Free Copy of KNIME Beginner’s Luck Book
at KNIME Press
https://www.knime.org/knimepress
Promotion Code:
ODSCLondonMeetup

Knime customer intelligence on social edia

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