Social Data Analytics Tool: Design, Development and Demonstrative Case Studies

Abid Hussain; Ravi Vatrapu

doi:10.1109/EDOCW.2014.70

Social Data Analytics Tool: Design, Development and Demonstrative Case Studies

Abid Hussain, Ravi Vatrapu

Norges Informasjonsteknologiske Høgskole

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

Abstract

This paper presents the design, development and demonstrative case studies of the Social Data Analytics Tool, SODATO. Adopting Action Design Framework [1], the objective of SODATO [2] is to collect, store, analyze, and report big social data emanating from the social media engagement of and social media conversations about organizations. We report and discuss results from two demonstrative case studies that were conducted using SODATO and conclude with implications and future work.

Original language	English
Title of host publication	Proceedings. IEEE 18th International Enterprise Distributed Object Computing. Workshops and Demonstrations, EDOC 2014
Editors	Georg Grossmann, Sylvain Hallé, Dimka Karastoyanova, Manfred Reichert, Stefanie Rinderle-Ma
Number of pages	5
Place of Publication	Los Alamitos, CA
Publisher	IEEE
Publication date	2014
Pages	414-417
Article number	6975394
ISBN (Print)	9781479954704
DOIs	https://doi.org/10.1109/EDOCW.2014.70
Publication status	Published - 2014
Event	The 18th IEEE Enterprise Computing Conference. EDOC 2014: Utilizing Big Data for the Enterprise of the Future - Ulm, Germany Duration: 1 Sept 2014 → 5 Sept 2014 Conference number: 18 http://www.edoc2014.org/

Conference

Conference	The 18th IEEE Enterprise Computing Conference. EDOC 2014
Number	18
Country/Territory	Germany
City	Ulm
Period	01/09/2014 → 05/09/2014
Internet address	http://www.edoc2014.org/

Series	International Enterprise Distributed Object Computing Conference. Proceedings
Volume	18
ISSN	1541-7719

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10.1109/EDOCW.2014.70Licence: Unspecified

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Hussain, A., & Vatrapu, R. (2014). Social Data Analytics Tool: Design, Development and Demonstrative Case Studies. In G. Grossmann, S. Hallé, D. Karastoyanova, M. Reichert, & S. Rinderle-Ma (Eds.), Proceedings. IEEE 18th International Enterprise Distributed Object Computing. Workshops and Demonstrations, EDOC 2014 (pp. 414-417). Article 6975394 IEEE. https://doi.org/10.1109/EDOCW.2014.70

Hussain, Abid ; Vatrapu, Ravi. / Social Data Analytics Tool : Design, Development and Demonstrative Case Studies. Proceedings. IEEE 18th International Enterprise Distributed Object Computing. Workshops and Demonstrations, EDOC 2014. editor / Georg Grossmann ; Sylvain Hallé ; Dimka Karastoyanova ; Manfred Reichert ; Stefanie Rinderle-Ma. Los Alamitos, CA : IEEE, 2014. pp. 414-417 (International Enterprise Distributed Object Computing Conference. Proceedings, Vol. 18).

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title = "Social Data Analytics Tool: Design, Development and Demonstrative Case Studies",

abstract = "This paper presents the design, development and demonstrative case studies of the Social Data Analytics Tool, SODATO. Adopting Action Design Framework [1], the objective of SODATO [2] is to collect, store, analyze, and report big social data emanating from the social media engagement of and social media conversations about organizations. We report and discuss results from two demonstrative case studies that were conducted using SODATO and conclude with implications and future work.",

keywords = "Data science, Computational social science, Social data analytics, Social graph, Social text",

author = "Abid Hussain and Ravi Vatrapu",

year = "2014",

doi = "10.1109/EDOCW.2014.70",

language = "English",

isbn = "9781479954704",

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pages = "414--417",

editor = "Georg Grossmann and Sylvain Hall{\'e} and Dimka Karastoyanova and Manfred Reichert and Stefanie Rinderle-Ma",

booktitle = "Proceedings. IEEE 18th International Enterprise Distributed Object Computing. Workshops and Demonstrations, EDOC 2014",

publisher = "IEEE",

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note = "The 18th IEEE Enterprise Computing Conference. EDOC 2014 ; Conference date: 01-09-2014 Through 05-09-2014",

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Hussain, A & Vatrapu, R 2014, Social Data Analytics Tool: Design, Development and Demonstrative Case Studies. in G Grossmann, S Hallé, D Karastoyanova, M Reichert & S Rinderle-Ma (eds), Proceedings. IEEE 18th International Enterprise Distributed Object Computing. Workshops and Demonstrations, EDOC 2014., 6975394, IEEE, Los Alamitos, CA, International Enterprise Distributed Object Computing Conference. Proceedings, vol. 18, pp. 414-417, The 18th IEEE Enterprise Computing Conference. EDOC 2014, Ulm, Germany, 01/09/2014. https://doi.org/10.1109/EDOCW.2014.70

Social Data Analytics Tool: Design, Development and Demonstrative Case Studies. / Hussain, Abid ; Vatrapu, Ravi.
Proceedings. IEEE 18th International Enterprise Distributed Object Computing. Workshops and Demonstrations, EDOC 2014. ed. / Georg Grossmann; Sylvain Hallé; Dimka Karastoyanova; Manfred Reichert; Stefanie Rinderle-Ma. Los Alamitos, CA: IEEE, 2014. p. 414-417 6975394 (International Enterprise Distributed Object Computing Conference. Proceedings, Vol. 18).

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

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AB - This paper presents the design, development and demonstrative case studies of the Social Data Analytics Tool, SODATO. Adopting Action Design Framework [1], the objective of SODATO [2] is to collect, store, analyze, and report big social data emanating from the social media engagement of and social media conversations about organizations. We report and discuss results from two demonstrative case studies that were conducted using SODATO and conclude with implications and future work.

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KW - Computational social science

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KW - Social graph

KW - Social text

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DO - 10.1109/EDOCW.2014.70

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Hussain A , Vatrapu R. Social Data Analytics Tool: Design, Development and Demonstrative Case Studies. In Grossmann G, Hallé S, Karastoyanova D, Reichert M, Rinderle-Ma S, editors, Proceedings. IEEE 18th International Enterprise Distributed Object Computing. Workshops and Demonstrations, EDOC 2014. Los Alamitos, CA: IEEE. 2014. p. 414-417. 6975394. (International Enterprise Distributed Object Computing Conference. Proceedings, Vol. 18). doi: 10.1109/EDOCW.2014.70