A Big Social Media Data Study of the 2017 German Federal Election Based on Social Set Analysis of Political Party Facebook Pages with SoSeVi

Benjamin Flesch; Ravi Vatrapu; Raghava Rao Mukkamala

doi:10.1109/BigData.2017.8258236

A Big Social Media Data Study of the 2017 German Federal Election Based on Social Set Analysis of Political Party Facebook Pages with SoSeVi

Benjamin Flesch, Ravi Vatrapu, Raghava Rao Mukkamala

Department of Digitalization

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

Abstract

We present a big social media data study that comprises of 1 million individuals who interact with Facebook pages of the seven major political parties CDU, CSU, SPD, FDP, Greens, Die Linke and AfD during the 2017 German federal election. Our study uses the Social Set Analysis (SSA) approach, which is based on the sociology of associations, mathematics of set theory, and advanced visual analytics of event studies. We illustrate the capabilities of SSA through the most recent version of our Social Set Analysis (SoSeVi) tool, which enables us to deep dive into Facebook activity concerning the election. We explore a significant gender-based difference between female and male interactions with political party Facebook pages. Furthermore, we perform a multi-faceted analysis of social media interactions using gender detection, user segmentation and retention analysis, and visualize our findings. In conclusion, we discuss the analytical approach of social set analysis and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology.

Original language	English
Title of host publication	Proceedings. 2017 IEEE International Conference on Big Data : IEEE Big Data 2017
Editors	Jian-Yun Nie, Zoran Obradovic, Toyotaro Suzumura, Rumi Ghosh, Raghunath Nambiar, Chonggang Wang, Hui Zang, Ricardo Baeza-Yates, Xiaohua Hu, Jeremy Kepner, Alfredo Cuzzocrea, Jian Tang, Masashi Toyoda
Number of pages	10
Place of Publication	Los Alamitos, CA
Publisher	IEEE
Publication date	2017
Pages	2720-2729
ISBN (Print)	9781538627167
ISBN (Electronic)	9781538627150, 9781538627143
DOIs	https://doi.org/10.1109/BigData.2017.8258236
Publication status	Published - 2017
Event	Fifth IEEE International Conference on Big Data. IEEE BigData 2017 - Boston, United States Duration: 11 Dec 2017 → 14 Dec 2017 Conference number: 5 http://cci.drexel.edu/bigdata/bigdata2017/

Conference

Conference	Fifth IEEE International Conference on Big Data. IEEE BigData 2017
Number	5
Country/Territory	United States
City	Boston
Period	11/12/2017 → 14/12/2017
Internet address	http://cci.drexel.edu/bigdata/bigdata2017/

Keywords

Big social media data
Social set analysis
Big data visual analytics
Facebook
2017 German federal election
Bundestagswahl
CDU
CSU
SPD
FDP
Grüne
AfD
Linke

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Flesch, B., Vatrapu, R., & Mukkamala, R. R. (2017). A Big Social Media Data Study of the 2017 German Federal Election Based on Social Set Analysis of Political Party Facebook Pages with SoSeVi. In J.-Y. Nie, Z. Obradovic, T. Suzumura, R. Ghosh, R. Nambiar, C. Wang, H. Zang, R. Baeza-Yates, X. Hu, J. Kepner, A. Cuzzocrea, J. Tang, & M. Toyoda (Eds.), Proceedings. 2017 IEEE International Conference on Big Data: IEEE Big Data 2017 (pp. 2720-2729). IEEE. https://doi.org/10.1109/BigData.2017.8258236

Flesch, Benjamin ; Vatrapu, Ravi ; Mukkamala, Raghava Rao. / A Big Social Media Data Study of the 2017 German Federal Election Based on Social Set Analysis of Political Party Facebook Pages with SoSeVi. Proceedings. 2017 IEEE International Conference on Big Data: IEEE Big Data 2017. editor / Jian-Yun Nie ; Zoran Obradovic ; Toyotaro Suzumura ; Rumi Ghosh ; Raghunath Nambiar ; Chonggang Wang ; Hui Zang ; Ricardo Baeza-Yates ; Xiaohua Hu ; Jeremy Kepner ; Alfredo Cuzzocrea ; Jian Tang ; Masashi Toyoda. Los Alamitos, CA : IEEE, 2017. pp. 2720-2729

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title = "A Big Social Media Data Study of the 2017 German Federal Election Based on Social Set Analysis of Political Party Facebook Pages with SoSeVi",

abstract = "We present a big social media data study that comprises of 1 million individuals who interact with Facebook pages of the seven major political parties CDU, CSU, SPD, FDP, Greens, Die Linke and AfD during the 2017 German federal election. Our study uses the Social Set Analysis (SSA) approach, which is based on the sociology of associations, mathematics of set theory, and advanced visual analytics of event studies. We illustrate the capabilities of SSA through the most recent version of our Social Set Analysis (SoSeVi) tool, which enables us to deep dive into Facebook activity concerning the election. We explore a significant gender-based difference between female and male interactions with political party Facebook pages. Furthermore, we perform a multi-faceted analysis of social media interactions using gender detection, user segmentation and retention analysis, and visualize our findings. In conclusion, we discuss the analytical approach of social set analysis and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology.",

keywords = "Big social media data, Social set analysis, Big data visual analytics, Facebook, 2017 German federal election, Bundestagswahl, CDU, CSU, SPD, FDP, Gr{\"u}ne, AfD, Linke, Big social media data, Social set analysis, Big data visual analytics, Facebook, 2017 German federal election, Bundestagswahl, CDU, CSU, SPD, FDP, Gr{\"u}ne, AfD, Linke",

author = "Benjamin Flesch and Ravi Vatrapu and Mukkamala, {Raghava Rao}",

year = "2017",

doi = "10.1109/BigData.2017.8258236",

language = "English",

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pages = "2720--2729",

editor = "Jian-Yun Nie and Zoran Obradovic and Toyotaro Suzumura and Rumi Ghosh and Raghunath Nambiar and Chonggang Wang and Hui Zang and Ricardo Baeza-Yates and Xiaohua Hu and Jeremy Kepner and Alfredo Cuzzocrea and Jian Tang and Masashi Toyoda",

booktitle = "Proceedings. 2017 IEEE International Conference on Big Data",

publisher = "IEEE",

address = "United States",

note = "Fifth IEEE International Conference on Big Data. IEEE BigData 2017 ; Conference date: 11-12-2017 Through 14-12-2017",

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Flesch, B, Vatrapu, R & Mukkamala, RR 2017, A Big Social Media Data Study of the 2017 German Federal Election Based on Social Set Analysis of Political Party Facebook Pages with SoSeVi. in J-Y Nie, Z Obradovic, T Suzumura, R Ghosh, R Nambiar, C Wang, H Zang, R Baeza-Yates, X Hu, J Kepner, A Cuzzocrea, J Tang & M Toyoda (eds), Proceedings. 2017 IEEE International Conference on Big Data: IEEE Big Data 2017. IEEE, Los Alamitos, CA, pp. 2720-2729, Fifth IEEE International Conference on Big Data. IEEE BigData 2017, Boston, Massachusetts, United States, 11/12/2017. https://doi.org/10.1109/BigData.2017.8258236

A Big Social Media Data Study of the 2017 German Federal Election Based on Social Set Analysis of Political Party Facebook Pages with SoSeVi. / Flesch, Benjamin; Vatrapu, Ravi ; Mukkamala, Raghava Rao.
Proceedings. 2017 IEEE International Conference on Big Data: IEEE Big Data 2017. ed. / Jian-Yun Nie; Zoran Obradovic; Toyotaro Suzumura; Rumi Ghosh; Raghunath Nambiar; Chonggang Wang; Hui Zang; Ricardo Baeza-Yates; Xiaohua Hu; Jeremy Kepner; Alfredo Cuzzocrea; Jian Tang; Masashi Toyoda. Los Alamitos, CA: IEEE, 2017. p. 2720-2729.

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

TY - GEN

T1 - A Big Social Media Data Study of the 2017 German Federal Election Based on Social Set Analysis of Political Party Facebook Pages with SoSeVi

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AU - Vatrapu, Ravi

AU - Mukkamala, Raghava Rao

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PY - 2017

Y1 - 2017

N2 - We present a big social media data study that comprises of 1 million individuals who interact with Facebook pages of the seven major political parties CDU, CSU, SPD, FDP, Greens, Die Linke and AfD during the 2017 German federal election. Our study uses the Social Set Analysis (SSA) approach, which is based on the sociology of associations, mathematics of set theory, and advanced visual analytics of event studies. We illustrate the capabilities of SSA through the most recent version of our Social Set Analysis (SoSeVi) tool, which enables us to deep dive into Facebook activity concerning the election. We explore a significant gender-based difference between female and male interactions with political party Facebook pages. Furthermore, we perform a multi-faceted analysis of social media interactions using gender detection, user segmentation and retention analysis, and visualize our findings. In conclusion, we discuss the analytical approach of social set analysis and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology.

AB - We present a big social media data study that comprises of 1 million individuals who interact with Facebook pages of the seven major political parties CDU, CSU, SPD, FDP, Greens, Die Linke and AfD during the 2017 German federal election. Our study uses the Social Set Analysis (SSA) approach, which is based on the sociology of associations, mathematics of set theory, and advanced visual analytics of event studies. We illustrate the capabilities of SSA through the most recent version of our Social Set Analysis (SoSeVi) tool, which enables us to deep dive into Facebook activity concerning the election. We explore a significant gender-based difference between female and male interactions with political party Facebook pages. Furthermore, we perform a multi-faceted analysis of social media interactions using gender detection, user segmentation and retention analysis, and visualize our findings. In conclusion, we discuss the analytical approach of social set analysis and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology.

KW - Big social media data

KW - Social set analysis

KW - Big data visual analytics

KW - Facebook

KW - 2017 German federal election

KW - Bundestagswahl

KW - CDU

KW - CSU

KW - SPD

KW - FDP

KW - Grüne

KW - AfD

KW - Linke

KW - Big social media data

KW - Social set analysis

KW - Big data visual analytics

KW - Facebook

KW - 2017 German federal election

KW - Bundestagswahl

KW - CDU

KW - CSU

KW - SPD

KW - FDP

KW - Grüne

KW - AfD

KW - Linke

U2 - 10.1109/BigData.2017.8258236

DO - 10.1109/BigData.2017.8258236

M3 - Article in proceedings

SN - 9781538627167

SP - 2720

EP - 2729

BT - Proceedings. 2017 IEEE International Conference on Big Data

A2 - Nie, Jian-Yun

A2 - Obradovic, Zoran

A2 - Suzumura, Toyotaro

A2 - Ghosh, Rumi

A2 - Nambiar, Raghunath

A2 - Wang, Chonggang

A2 - Zang, Hui

A2 - Baeza-Yates, Ricardo

A2 - Hu, Xiaohua

A2 - Kepner, Jeremy

A2 - Cuzzocrea, Alfredo

A2 - Tang, Jian

A2 - Toyoda, Masashi

PB - IEEE

CY - Los Alamitos, CA

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Y2 - 11 December 2017 through 14 December 2017

ER -

Flesch B, Vatrapu R , Mukkamala RR. A Big Social Media Data Study of the 2017 German Federal Election Based on Social Set Analysis of Political Party Facebook Pages with SoSeVi. In Nie JY, Obradovic Z, Suzumura T, Ghosh R, Nambiar R, Wang C, Zang H, Baeza-Yates R, Hu X, Kepner J, Cuzzocrea A, Tang J, Toyoda M, editors, Proceedings. 2017 IEEE International Conference on Big Data: IEEE Big Data 2017. Los Alamitos, CA: IEEE. 2017. p. 2720-2729 doi: 10.1109/BigData.2017.8258236