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

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-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.
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.
LanguageEnglish
Title of host publicationProceedings. 2017 IEEE International Conference on Big Data : IEEE Big Data 2017
EditorsJian-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
Place of PublicationLos Alamitos, CA
PublisherIEEE
Date2017
Pages2638-2647
ISBN (Print)9781538627167
ISBN (Electronic)9781538627150, 9781538627143
DOIs
StatePublished - 2017
Event5th IEEE International Conference on Big Data. 2017 - Boston, United States
Duration: 11 Dec 201714 Dec 2017
Conference number: 5
http://cci.drexel.edu/bigdata/bigdata2017/

Conference

Conference5th IEEE International Conference on Big Data. 2017
Number5
CountryUnited States
CityBoston
Period11/12/201714/12/2017
Internet address

Bibliographical note

CBS Library does not have access to the material

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

Cite this

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. 2638-2647). Los Alamitos, CA: IEEE. DOI: 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. 2638-2647
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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}",
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year = "2017",
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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",
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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. 2638-2647, Boston, United States, 11/12/2017. 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. / 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. 2638-2647.

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

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N1 - CBS Library does not have access to the material

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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.

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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 J-Y, 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. 2638-2647. Available from, DOI: 10.1109/BigData.2017.8258236