Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    unusual trading activity
    Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
    3 Min Read
    software developer using ai
    How Data Analytics Helps Developers Deliver Better Tech Services
    8 Min Read
    ai for stock trading
    Can Data Analytics Help Investors Outperform Warren Buffett
    9 Min Read
    media monitoring
    Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
    5 Min Read
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Predictive Analytics and Politics – Part 2
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Mining > Predictive Analytics and Politics – Part 2
Data Mining

Predictive Analytics and Politics – Part 2

ThemosKalafatis
ThemosKalafatis
5 Min Read
SHARE

In the previous post we have seen an example of analyzing messages sent from citizens regarding a new taxation plan. We identified some correlations between keywords and concepts but there are more ways to gain knowledge from such unstructured information.
By using Cluster Analysis we can extract groups of similar concepts among thousands of comments written by citizens but also presenting an order within them. Let’s assume that Cluster Analysis reveals the following clusters (or similar concepts) within submitted messages :
  • battling tax fraud
  • requests for a fair tax plan
  • requests for less taxation for large families
  • various incentives for citizens
Our problem is finding the order of importance that people place on the various concept categories shown above : Is battling tax fraud considered more important (=discussed more frequently by citizens) than requesting a fair tax plan? How about taxation for larger families?
A cluster analysis can reveal to us the size of each cluster and -as a consequence- how important each cluster is :

 

 

We make the assumption that in the text representation shown above …

More Read

Five Subscription Page Absolutes: Ask for the Right Information
Warranty Management – New rules to apply
EDM Summit – some closing thoughts
“The consulting business may drive sales for a lot of IBM’s own technologies, as well. The company…”
5 ways to reduce cost with predictive analytics
In the previous post we have seen an example of analyzing messages sent from
citizens regarding a new taxation plan. We identified some correlations
between keywords and concepts but there are more ways to gain knowledge
from such unstructured information.
By using Cluster
Analysis we can extract groups of similar concepts among thousands of
comments written by citizens but also presenting an order within them.
Let’s assume that Cluster Analysis reveals the following clusters (or
similar concepts) within submitted messages :
  • battling tax fraud
  • requests for a fair tax plan
  • requests for less taxation for large families
  • various incentives for citizens
Our problem is finding the order of
importance that people place on the various concept categories shown
above : Is battling tax fraud considered more important (=discussed more
frequently by citizens) than requesting a fair tax plan? How about
taxation for larger families?
A cluster analysis can reveal to us the
size of each cluster and -as a consequence- how important each cluster
is :

 

 

We make the assumption that in the
text representation shown above Cluster 5 (which contains 329 citizen
messages) is about requests for a fair tax plan and Cluster 10 contains
messages with requests that tax fraud should be minimized. It appears
that significantly less people are concerned with a battle against
fraudulent activity but they request -more immediate- benefits through a
fair tax plan.
Collecting and analyzing information found
in blogs and forum entries is another area of analysis that could prove
very interesting. Let’s see an example with the Political / Social /
Economic situation in Greece : The goal is to identify and extract
trends and co-occurences of key concepts from blog titles and forum
posts such as :
  • Names of major Political parties
  • Names of Politicians
  • Economy (words/phrases such as “austerity
    plan”)
  • Negative
    characterizations
  • Company
    Names…etc
For
this kind of data several applications can emerge. We could track
specific concepts through time and see their trends. We can also
identify which concepts are discussed together. As an example we could
identify the reasons on why Giorgos Papandreou (PM of Greece) is
characterized in a negative way in blog posts. (= what other concepts are
found in Blog posts containing keywords ‘Giorgos Papandreou’ AND Bad
Characterizations?) :
(Note : PASOK = Governmental Political Party )
Politics
= 120
Economy=72
Economy, Politics=40
PASOK=24
Politics, PASOK, Referendum=8
Economy, Politics,PASOK,Referendum, Immigrants=8
Economy, Politics, Society=8
Society, PASOK=4
In other words : Giorgos Papandreou is
criticized mainly for his Political decisions and the Economy followed
by criticism on PASOK. Negative sentiment also exists because of the
fact that a percentage of Greek citizens require that a referendum
should take place concerning the latest decision of the Greek government
to give to a large proportion of Immigrants the Greek citizenship.
TAGGED:cluster analysisdata miningpoliticspredictive analytics
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

0622cae5 f7d7 4f74 84b5 eabd1a823dca
How Data-Driven Grocery Recommendations Help Shoppers Eat Better With Less Effort
Big Data Exclusive
business recovering from data loss
How Data-Driven Businesses Protect MySQL Databases from Shutdown
Big Data Exclusive
ai driven task management
Reducing “Work About Work” with AI Task Managers
Artificial Intelligence Exclusive
data center uptime
Why Rodent-Resistant Conduits Are Critical for Data Center Uptime
Big Data Data Management Exclusive Risk Management

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

predictive analytics helps Albanian bitcoin investors
Blockchain

Albanian Bitcoin Investors Tap the Power of Predictive Analytics

9 Min Read
surveys data
Data Mining

5 Data Mining Tips to Leverage the Benefits of Surveys

11 Min Read

Questions about analytics?

3 Min Read
amazon analytics big data use
AnalyticsBig DataBusiness IntelligenceCloud ComputingData MiningITPredictive AnalyticsWeb Analytics

How Amazon Uses Big Data to Boost Its Performance

6 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive
ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?