Volkswagen’s Diesel Emission Scandal: Analysis of Facebook Engagement and Financial Outcomes

Qi An, Morten Grimmig Christensen, Annith Ramachandran, Raghava Rao Mukkamala, Ravi Vatrapu

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This paper investigates Volkswagen’s diesel scandal with a focus on the relationship between their Facebook engagement and financial performance during the period of 2012–16. We employ the big social data analytics approaches of visual and text analytics on Volkswagen’s Facebook data and financial reporting data. We specifically analyze the potential effects on the company in the diesel emission scandal years of 2014–2016. We find that the diesel emission scandal had the most impact in the short-term period immediately after its occurrence resulting in Facebook users reacting negatively against Volkswagen but also some users defending the company. In the long-term, it seems that the scandal has not impacted the company based on the analysis of both their financial data and their social media data.
This paper investigates Volkswagen’s diesel scandal with a focus on the relationship between their Facebook engagement and financial performance during the period of 2012–16. We employ the big social data analytics approaches of visual and text analytics on Volkswagen’s Facebook data and financial reporting data. We specifically analyze the potential effects on the company in the diesel emission scandal years of 2014–2016. We find that the diesel emission scandal had the most impact in the short-term period immediately after its occurrence resulting in Facebook users reacting negatively against Volkswagen but also some users defending the company. In the long-term, it seems that the scandal has not impacted the company based on the analysis of both their financial data and their social media data.
LanguageEnglish
Title of host publicationBig Data – BigData 2018 : 7th International Congress, Held as Part of the Services Conference Federation, SCF 2018, Seattle, WA, USA, June 25–30, 2018, Proceedings
EditorsFrancis Y. L. Chin, C. L. Philip Chen, Latifur Khan, Kisung Lee, Liang-Jie Zhang
Place of PublicationCham
PublisherSpringer
Date2018
Pages260-276
ISBN (Print)9783319943008
ISBN (Electronic)9783319943015
DOIs
StatePublished - 2018
Event7th International Congress on Big Data. BigData 2018: Held as Part of the Services Conference Federation, SCF 2018 - Seattle, United States
Duration: 25 Jun 201830 Jun 2018
Conference number: 7
http://bigdatacongress.org/2018/index.html

Conference

Conference7th International Congress on Big Data. BigData 2018
Number7
CountryUnited States
CitySeattle
Period25/06/201830/06/2018
Internet address
SeriesLecture Notes in Computer Science
Volume10968
ISSN0302-9743

Cite this

An, Q., Grimmig Christensen, M., Ramachandran, A., Mukkamala, R. R., & Vatrapu, R. (2018). Volkswagen’s Diesel Emission Scandal: Analysis of Facebook Engagement and Financial Outcomes. In F. Y. L. Chin, C. L. P. Chen, L. Khan, K. Lee, & L-J. Zhang (Eds.), Big Data – BigData 2018: 7th International Congress, Held as Part of the Services Conference Federation, SCF 2018, Seattle, WA, USA, June 25–30, 2018, Proceedings (pp. 260-276). Cham: Springer. Lecture Notes in Computer Science, Vol.. 10968, DOI: 10.1007/978-3-319-94301-5_20
An, Qi ; Grimmig Christensen, Morten ; Ramachandran, Annith ; Mukkamala, Raghava Rao ; Vatrapu, Ravi. / Volkswagen’s Diesel Emission Scandal : Analysis of Facebook Engagement and Financial Outcomes. Big Data – BigData 2018: 7th International Congress, Held as Part of the Services Conference Federation, SCF 2018, Seattle, WA, USA, June 25–30, 2018, Proceedings. editor / Francis Y. L. Chin ; C. L. Philip Chen ; Latifur Khan ; Kisung Lee ; Liang-Jie Zhang. Cham : Springer, 2018. pp. 260-276 (Lecture Notes in Computer Science, ???volume??? 10968).
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title = "Volkswagen’s Diesel Emission Scandal: Analysis of Facebook Engagement and Financial Outcomes",
abstract = "This paper investigates Volkswagen’s diesel scandal with a focus on the relationship between their Facebook engagement and financial performance during the period of 2012–16. We employ the big social data analytics approaches of visual and text analytics on Volkswagen’s Facebook data and financial reporting data. We specifically analyze the potential effects on the company in the diesel emission scandal years of 2014–2016. We find that the diesel emission scandal had the most impact in the short-term period immediately after its occurrence resulting in Facebook users reacting negatively against Volkswagen but also some users defending the company. In the long-term, it seems that the scandal has not impacted the company based on the analysis of both their financial data and their social media data.",
author = "Qi An and {Grimmig Christensen}, Morten and Annith Ramachandran and Mukkamala, {Raghava Rao} and Ravi Vatrapu",
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language = "English",
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booktitle = "Big Data – BigData 2018",
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An, Q, Grimmig Christensen, M, Ramachandran, A, Mukkamala, RR & Vatrapu, R 2018, Volkswagen’s Diesel Emission Scandal: Analysis of Facebook Engagement and Financial Outcomes. in FYL Chin, CLP Chen, L Khan, K Lee & L-J Zhang (eds), Big Data – BigData 2018: 7th International Congress, Held as Part of the Services Conference Federation, SCF 2018, Seattle, WA, USA, June 25–30, 2018, Proceedings. Springer, Cham, Lecture Notes in Computer Science, vol. 10968, pp. 260-276, Seattle, United States, 25/06/2018. DOI: 10.1007/978-3-319-94301-5_20

Volkswagen’s Diesel Emission Scandal : Analysis of Facebook Engagement and Financial Outcomes. / An, Qi; Grimmig Christensen, Morten; Ramachandran, Annith; Mukkamala, Raghava Rao; Vatrapu, Ravi.

Big Data – BigData 2018: 7th International Congress, Held as Part of the Services Conference Federation, SCF 2018, Seattle, WA, USA, June 25–30, 2018, Proceedings. ed. / Francis Y. L. Chin; C. L. Philip Chen; Latifur Khan; Kisung Lee; Liang-Jie Zhang. Cham : Springer, 2018. p. 260-276.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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AU - Vatrapu,Ravi

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N2 - This paper investigates Volkswagen’s diesel scandal with a focus on the relationship between their Facebook engagement and financial performance during the period of 2012–16. We employ the big social data analytics approaches of visual and text analytics on Volkswagen’s Facebook data and financial reporting data. We specifically analyze the potential effects on the company in the diesel emission scandal years of 2014–2016. We find that the diesel emission scandal had the most impact in the short-term period immediately after its occurrence resulting in Facebook users reacting negatively against Volkswagen but also some users defending the company. In the long-term, it seems that the scandal has not impacted the company based on the analysis of both their financial data and their social media data.

AB - This paper investigates Volkswagen’s diesel scandal with a focus on the relationship between their Facebook engagement and financial performance during the period of 2012–16. We employ the big social data analytics approaches of visual and text analytics on Volkswagen’s Facebook data and financial reporting data. We specifically analyze the potential effects on the company in the diesel emission scandal years of 2014–2016. We find that the diesel emission scandal had the most impact in the short-term period immediately after its occurrence resulting in Facebook users reacting negatively against Volkswagen but also some users defending the company. In the long-term, it seems that the scandal has not impacted the company based on the analysis of both their financial data and their social media data.

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An Q, Grimmig Christensen M, Ramachandran A, Mukkamala RR, Vatrapu R. Volkswagen’s Diesel Emission Scandal: Analysis of Facebook Engagement and Financial Outcomes. In Chin FYL, Chen CLP, Khan L, Lee K, Zhang L-J, editors, Big Data – BigData 2018: 7th International Congress, Held as Part of the Services Conference Federation, SCF 2018, Seattle, WA, USA, June 25–30, 2018, Proceedings. Cham: Springer. 2018. p. 260-276. (Lecture Notes in Computer Science, Vol. 10968). Available from, DOI: 10.1007/978-3-319-94301-5_20