India Elections 2014: Time-Lagged Correlation between Media Bias and Facebook Trend

Francis P. Barclay; C. Pichandy; Anusha Venkat

India Elections 2014: Time-Lagged Correlation between Media Bias and Facebook Trend

Francis P. Barclay * §

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C. Pichandy

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Anusha Venkat

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§ PSG College of Arts and Science

India Elections 2014: Time-Lagged Correlation between Media Bias and Facebook Trend

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Abstract

After establishing print media bias and Facebook trend as reliable predictors of election outcome, the study analyses the relationship between the two before and during the 2014 Indian Lok Sabha election. Time-lagged correlation is used to study the immediate effect of newspaper reports on the political behaviour of Facebook. Further, a correlation was found to exist between the long-term political trends in the print media and Facebook. That is, the number of positive and negative news reports published on a party in the newspapers affected the number of ‘likes’ recorded on the Facebook fan page of the party or its candidate.

References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Francis P. Barclay, C. Pichandy, Anusha Venkat. 2015. "India Elections 2014: Time-Lagged Correlation between Media Bias and Facebook Trend". Global Journal of Human-Social Science - A: Arts & Humanities GJHSS-A Volume 15 (GJHSS Volume 15 Issue A2).

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Journal Specifications

Crossref Journal DOI 10.17406/GJHSS

Print ISSN 0975-587X

e-ISSN 2249-460X

Keywords

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Classification

GJHSS-A Classification FOR Code: 200199

Submission ReceivedApril 8, 2015
Peer Review Double Blind
Handling Editor
Accepted May 5, 2015
Published May 15, 2015

Version of record

v1.2

Issue date

March 19, 2015

Language

English

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Article Matrices

Total Score: 103

Country: India

Subject: Global Journal of Human-Social Science

Authors: Francis P. Barclay, C. Pichandy, Anusha Venkat (PhD/Dr. count: 0)

View Count (all-time): 319

Total Views (Real + Logic): 1917

Total Downloads (simulated): 92

Publish Date: 2015 05, Fri

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Total Views: 1.9K

Total Downloads: 92

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