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Quantifying cross-platform engagement through large-scale user alignment

Published: 23 June 2014 Publication History

Abstract

As online social media becomes prevalent as part of our daily life, it is increasingly common for a user to have accounts on multiple social media platforms. In this work, we present our findings on quantifying the extent of user engagement of different platforms as well as their correlations. The study is conducted based on a large-scale user alignment on 6 major social media platforms. Specifically, we identify both explicit and implicit mentions of social media accounts from the Twitter Decahose stream over a period of 22 months. During the process, we have aligned a total of 21,456,808 Twitter users to their alternative accounts on different platforms. Subsequently, we extract the number of overlapping users between any combination of these social media platforms exhaustively.

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Cited By

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  • (2020)Robust and Scalable Entity Alignment in Big Data2020 IEEE International Conference on Big Data (Big Data)10.1109/BigData50022.2020.9378273(2526-2533)Online publication date: 10-Dec-2020
  • (2018)Editorial of the Special Issue on Following User Pathways: Key Contributions and Future Directions in Cross-Platform Social Media ResearchInternational Journal of Human–Computer Interaction10.1080/10447318.2018.147157534:10(895-912)Online publication date: 29-May-2018
  • (2017)Characterizing Regional and Behavioral Device Variations Across the Twitter TimelineProceedings of the 2017 ACM on Web Science Conference10.1145/3091478.3091498(279-288)Online publication date: 25-Jun-2017
  • Show More Cited By

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  1. Quantifying cross-platform engagement through large-scale user alignment

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      cover image ACM Conferences
      WebSci '14: Proceedings of the 2014 ACM conference on Web science
      June 2014
      318 pages
      ISBN:9781450326223
      DOI:10.1145/2615569
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 23 June 2014

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      Author Tags

      1. human behavior
      2. measurement

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      • Poster

      Funding Sources

      • Intelligence Advanced Research Projects Activity (IARPA) via Department of Interior National Business Center (DoI / NBC)

      Conference

      WebSci '14
      Sponsor:
      WebSci '14: ACM Web Science Conference
      June 23 - 26, 2014
      Indiana, Bloomington, USA

      Acceptance Rates

      WebSci '14 Paper Acceptance Rate 29 of 144 submissions, 20%;
      Overall Acceptance Rate 245 of 933 submissions, 26%

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      Cited By

      View all
      • (2020)Robust and Scalable Entity Alignment in Big Data2020 IEEE International Conference on Big Data (Big Data)10.1109/BigData50022.2020.9378273(2526-2533)Online publication date: 10-Dec-2020
      • (2018)Editorial of the Special Issue on Following User Pathways: Key Contributions and Future Directions in Cross-Platform Social Media ResearchInternational Journal of Human–Computer Interaction10.1080/10447318.2018.147157534:10(895-912)Online publication date: 29-May-2018
      • (2017)Characterizing Regional and Behavioral Device Variations Across the Twitter TimelineProceedings of the 2017 ACM on Web Science Conference10.1145/3091478.3091498(279-288)Online publication date: 25-Jun-2017
      • (2016)Linking Online Identities and Content in Connectivist MOOCs across Multiple Social Media PlatformsProceedings of the 25th International Conference Companion on World Wide Web10.1145/2872518.2890458(483-488)Online publication date: 11-Apr-2016
      • (undefined)Platform Algorithms and Their Effect on Civic and Political ArenasSSRN Electronic Journal10.2139/ssrn.2607291

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