Analysis of Politics and Industry Nexus: India
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ANALYSIS OF POLITICS AND INDUSTRY NEXUS: INDIAProject Supervisor: Prof. Aaditeshwar Seth
Himanshu Sharma (2010CS50284)Mayank Srivastava (2010CS10224)
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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.
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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.
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SYSTEM IN DETAIL
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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.
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CORRELATION BETWEEN NEWSPAPERS Used Spearman’s rank correlation coefficient. High correlation when entities are ranked
using PageRank values. Correlation coefficients as on 1st 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: 0.99336
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CORRELATION BETWEEN NEWSPAPERS Low correlation when entities are ranked by
Fame values. Correlation coefficients as on 1st 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.
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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.
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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.
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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 Jinping, while the rest ignore him.
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TIMELINES SHOWING SOME IMPORTANT ENTITIES
Hindustan Times
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TIMELINES SHOWING SOME IMPORTANT ENTITIES
The Hindu
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TIMELINES SHOWING SOME IMPORTANT ENTITIES
The Times of India
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TIMELINES SHOWING SOME IMPORTANT ENTITIES
DNA (Political Section)
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TIMELINES SHOWING BIAS WITH POLITICAL PARTIES
Hindustan Times
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TIMELINES SHOWING BIAS WITH POLITICAL PARTIES
The Times of India
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TIMELINES SHOWING BIAS WITH POLITICAL PARTIES
DNA (Political Section)
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TIMELINES SHOWING BIAS WITH POLITICAL PARTIES
The Hindu
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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.
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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.
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Thank You