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  5. Road to the White House: Analyzing the Relations Between Mainstream and Social Media During the U.S. Presidential Primaries

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Preprint
English
2020

Road to the White House: Analyzing the Relations Between Mainstream and Social Media During the U.S. Presidential Primaries

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0 Files

$0 Value

English
2020
arXiv (Cornell University)
DOI: 10.48550/arxiv.2009.09307

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Hamid Reza Karimi
Hamid Reza Karimi

Politecnico di Milano

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Aaron Brookhouse
Tyler Derr
Hamid Reza Karimi
+2 more

Abstract

Information is crucial to the function of a democratic society where well-informed citizens can make rational political decisions. While in the past political entities were primarily utilizing newspaper and later television to inform the public, with the rise of the Internet and online social media, the political arena has transformed into a more complex structure. Now, more than ever, people express themselves online while mainstream news agencies attempt to seize the power of the Internet to spread their agenda. To grasp the political coexistence of mainstream media and online social media, in this paper, we perform an analysis between these two sources of information in the context of the U.S. 2020 presidential election. In particular, we collect data during the 2020 Democratic Party presidential primaries pertaining to the candidates and by analyzing this data, we highlight similarities and differences between these two main types of sources, detect the potential impact they have on each other, and understand how this impact relationship can change over time. To supplement these two main sources and to establish a baseline, we also include Google Trends search results and Polling results for each of the candidates that are being analyzed.

How to cite this publication

Aaron Brookhouse, Tyler Derr, Hamid Reza Karimi, H. Russell Bernard, Jiliang Tang (2020). Road to the White House: Analyzing the Relations Between Mainstream and Social Media During the U.S. Presidential Primaries. arXiv (Cornell University), DOI: 10.48550/arxiv.2009.09307.

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Publication Details

Type

Preprint

Year

2020

Authors

5

Datasets

0

Total Files

0

Language

English

Journal

arXiv (Cornell University)

DOI

10.48550/arxiv.2009.09307

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