The untold story of usa presidential elections in 2016 - Insights from twitter analytics

Purva Grover; Arpan Kumar Kar; Yogesh K. Dwivedi; Marijn Janssen

doi:10.1007/978-3-319-68557-1_30

The untold story of usa presidential elections in 2016 - Insights from twitter analytics

Purva Grover^*, Arpan Kumar Kar, Yogesh K. Dwivedi, Marijn Janssen

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Scopus citations

Abstract

Elections are the most critical events for any nation and paves the path for future growth and prosperity of the economy. Due to its high impact, a lot of discussions take place among all stakeholders in social media. In this study, we attempt to examine the discussions surrounding USA Election, 2016 in Twitter. Further we highlight some of the domains influencing the voter behaviour by applying the outcome of Twitter analytics to Newman and Sheth’s model of Voter Choice. Through the analysis of 784,153 tweets from 287,838 users over 18 weeks, we present interesting findings on what may have affected the polarization of USA elections.

Original language	English
Title of host publication	Digital Nations – Smart Cities, Innovation, and Sustainability - 16th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2017, Proceedings
Editors	Antonis Simintiras, Salah Al-Sharhan, Arpan Kumar Kar, P. Vigneswara Ilavarasan, M.P. Gupta, Matti Mantymaki, Yogesh K. Dwivedi, Marijn Janssen
Publisher	Springer Verlag
Pages	339-350
Number of pages	12
ISBN (Print)	9783319685564
DOIs	https://doi.org/10.1007/978-3-319-68557-1_30
State	Published - 2017
Externally published	Yes
Event	16th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2017 - Delhi, India Duration: 21 Nov 2017 → 23 Nov 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10595 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2017
Country/Territory	India
City	Delhi
Period	21/11/17 → 23/11/17

Bibliographical note

Publisher Copyright:
© IFIP International Federation for Information Processing 2017.

Keywords

Information propagation
Public policy
Social media
Social media analytics
Twitter analytics

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-68557-1_30

Cite this

Grover, P., Kar, A. K., Dwivedi, Y. K., & Janssen, M. (2017). The untold story of usa presidential elections in 2016 - Insights from twitter analytics. In A. Simintiras, S. Al-Sharhan, A. K. Kar, P. V. Ilavarasan, M. P. Gupta, M. Mantymaki, Y. K. Dwivedi, & M. Janssen (Eds.), Digital Nations – Smart Cities, Innovation, and Sustainability - 16th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2017, Proceedings (pp. 339-350). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10595 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-68557-1_30

Grover, Purva ; Kar, Arpan Kumar ; Dwivedi, Yogesh K. et al. / The untold story of usa presidential elections in 2016 - Insights from twitter analytics. Digital Nations – Smart Cities, Innovation, and Sustainability - 16th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2017, Proceedings. editor / Antonis Simintiras ; Salah Al-Sharhan ; Arpan Kumar Kar ; P. Vigneswara Ilavarasan ; M.P. Gupta ; Matti Mantymaki ; Yogesh K. Dwivedi ; Marijn Janssen. Springer Verlag, 2017. pp. 339-350 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "The untold story of usa presidential elections in 2016 - Insights from twitter analytics",

abstract = "Elections are the most critical events for any nation and paves the path for future growth and prosperity of the economy. Due to its high impact, a lot of discussions take place among all stakeholders in social media. In this study, we attempt to examine the discussions surrounding USA Election, 2016 in Twitter. Further we highlight some of the domains influencing the voter behaviour by applying the outcome of Twitter analytics to Newman and Sheth{\textquoteright}s model of Voter Choice. Through the analysis of 784,153 tweets from 287,838 users over 18 weeks, we present interesting findings on what may have affected the polarization of USA elections.",

keywords = "Information propagation, Public policy, Social media, Social media analytics, Twitter analytics",

author = "Purva Grover and Kar, \{Arpan Kumar\} and Dwivedi, \{Yogesh K.\} and Marijn Janssen",

note = "Publisher Copyright: {\textcopyright} IFIP International Federation for Information Processing 2017.; 16th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2017 ; Conference date: 21-11-2017 Through 23-11-2017",

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doi = "10.1007/978-3-319-68557-1\_30",

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Grover, P, Kar, AK, Dwivedi, YK & Janssen, M 2017, The untold story of usa presidential elections in 2016 - Insights from twitter analytics. in A Simintiras, S Al-Sharhan, AK Kar, PV Ilavarasan, MP Gupta, M Mantymaki, YK Dwivedi & M Janssen (eds), Digital Nations – Smart Cities, Innovation, and Sustainability - 16th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10595 LNCS, Springer Verlag, pp. 339-350, 16th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2017, Delhi, India, 21/11/17. https://doi.org/10.1007/978-3-319-68557-1_30

The untold story of usa presidential elections in 2016 - Insights from twitter analytics. / Grover, Purva; Kar, Arpan Kumar; Dwivedi, Yogesh K. et al.
Digital Nations – Smart Cities, Innovation, and Sustainability - 16th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2017, Proceedings. ed. / Antonis Simintiras; Salah Al-Sharhan; Arpan Kumar Kar; P. Vigneswara Ilavarasan; M.P. Gupta; Matti Mantymaki; Yogesh K. Dwivedi; Marijn Janssen. Springer Verlag, 2017. p. 339-350 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10595 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Grover, Purva

AU - Kar, Arpan Kumar

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AB - Elections are the most critical events for any nation and paves the path for future growth and prosperity of the economy. Due to its high impact, a lot of discussions take place among all stakeholders in social media. In this study, we attempt to examine the discussions surrounding USA Election, 2016 in Twitter. Further we highlight some of the domains influencing the voter behaviour by applying the outcome of Twitter analytics to Newman and Sheth’s model of Voter Choice. Through the analysis of 784,153 tweets from 287,838 users over 18 weeks, we present interesting findings on what may have affected the polarization of USA elections.

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A2 - Kar, Arpan Kumar

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Grover P, Kar AK, Dwivedi YK, Janssen M. The untold story of usa presidential elections in 2016 - Insights from twitter analytics. In Simintiras A, Al-Sharhan S, Kar AK, Ilavarasan PV, Gupta MP, Mantymaki M, Dwivedi YK, Janssen M, editors, Digital Nations – Smart Cities, Innovation, and Sustainability - 16th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2017, Proceedings. Springer Verlag. 2017. p. 339-350. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-68557-1_30

The untold story of usa presidential elections in 2016 - Insights from twitter analytics

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this