Project Supervisor Prof Aaditeshwar Seth Himanshu Sharma 2010CS50284 Mayank Srivastava 2010CS10224 Objectives Extract information about politicalindustry and intra political nexus from newspapers and some available structured sources on the web ID: 306888
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Slide1
Analysis of Politics and Industry Nexus: India
Project Supervisor: Prof.
Aaditeshwar
Seth
Himanshu
Sharma (2010CS50284)
Mayank
Srivastava
(2010CS10224
)Slide2
Objectives
Extract information about political-industry and intra political nexus from newspapers and some available structured sources on the web.
Represent it in the form of a graph with nodes representing entities and edges representing the relation between entities.
Analyze the graph obtained, rank the entities,
and find correlation between news in different newspapers.Slide3
Implementation
Structured information collected from netapedia.in, myneta.info, PPPIndia.com and capitaline.info.
Continuous RSS feed collection from different newspapers.
Processing of the news through an NLP tool,
OpenCalais
.
Storing information in database in tables, filtering it and ranking the entities.Slide4
System in DetailSlide5
Ranking of Entities
Ranking entities using exponential moving average (called Fame from now onwards), which is updated on occurrence basis: High sensitivity to changing news, important entities in news come up while less important ones go down.
Ranking using PageRank algorithm with the exponential moving average used as personalization vector: Low sensitivity to changing news, shows the overall influence of an entity in the network.Slide6
Correlation Between Newspapers
Used Spearman’s rank correlation coefficient.
High correlation when entities are ranked using PageRank values.
Correlation coefficients
as on
1
st
March (with respect to the overall data):
DNA (Business Section): 0.99118
Hindustan Times: 0.99147
DNA (Political Section): 0.99290
The Times of India: 0.99305
The Hindu: 0.99336Slide7
Correlation Between Newspapers
Low correlation when entities are ranked by Fame values.
Correlation coefficients
as on
1
st
March (with respect to the overall data):
DNA (Business Section):
0.33939
Hindustan Times:
0.41778
DNA (Political Section):
0.52837
The Times of India:
0.54673
The Hindu:
0.57951
Low correlation suggests that newspapers are biased.Slide8
More on Correlation
Plotted week to week correlation
Higher correlation between DNA (Business Section) and DNA (Political Section).
Hindu Shows a little lower correlation with Hindustan Times and The Times of India, showing some “different news from Times”.
Plotted inter-week correlation coefficients for newspaper: Mostly varies between 0.2 to 0.4
Increased time duration to see longevity of news. Correlation values reach an asymptotic value of around 0.15 for political newspapers.Slide9
More on Correlation
For DNA (Business section), correlation touches 0.05.
DNA (Business Section) has lowest maximum longevity- It frequently switches news.
Longevity lower in general for The Hindi and Hindustan Times, as compared to DNA (Political Section) and The Times of India.
DNA (Political Section) and TOI cling to the same news and repeat it through a prolonged duration, while HT and Hindu prefer to switch news.Slide10
Bias By Newspapers: Examples
In August 2012, TOI gives a lot of emphasis on
Nitish
Kumar; while Hindu chooses to neglect it.
During mid of March 2013, Hindu, Hindustan Times and DNA (Political Section) give a lot of emphasis on
Manmohan
Singh,but
The Times of India gives him less importance. Instead, it shows a number of news pertaining to Xi
J
inping
, while the rest ignore him.Slide11
Timelines Showing Some Important Entities
Hindustan TimesSlide12
Timelines Showing Some Important Entities
The HinduSlide13
Timelines Showing Some Important Entities
The Times of IndiaSlide14
Timelines Showing Some Important Entities
DNA (Political Section)Slide15
Timelines Showing Bias with Political Parties
Hindustan TimesSlide16
Timelines Showing Bias with Political Parties
The Times of IndiaSlide17
Timelines Showing Bias with Political Parties
DNA (Political Section)Slide18
Timelines Showing Bias with Political Parties
The HinduSlide19
Conclusions
The most important parts of news are shown almost equally by all newspapers.
Newspapers generally do biasing in showing the less important components of news.
Newspapers are generally biased in showing regional parties.
Janata
Dal (United) is given preference by TOI and DNA, while ignored by Hindu.
Both
Samajwadi
Party and
Akhilesh
yadav
are very clearly avoided by Hindustan Times.
CPI is closely followed by Hindu, while Shiv
Sena
is avoided by it.Slide20
References
www.visualdataweb.org/relfinder.php
www.mpi-inf.mpg.de/yago-naga/yago
www.dbpedia.org
www.opencalais.com
www.wikipedia.org
www.myneta.info
www.netapedia.in
www.semanticproxy.com
“Identifying
Influencers in Social
Networks”
by
Kushal
Dave,
Rushi
Bhatt,
VasudevaVarma
.Slide21
Thank You