Information flow on social networks: From empirical data to situation understanding

Heather Roy, Tarek Abdelzaher, Elizabeth K. Bowman, Md Tanvir Al Amin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes characteristics of information flow on social channels, as a function of content type and relations among individual sources, distilled from analysis of Twitter data as well as human subject survey results. The working hypothesis is that individuals who propagate content on social media act (e.g., decide whether to relay information or not) in accordance with their understanding of the content, as well as their own beliefs and trust relations. Hence, the resulting aggregate content propagation pattern encodes the collective content interpretation of the underlying group, as well as their relations. Analysis algorithms are described to recover such relations from the observed propagation patterns as well as improve our understanding of the content itself in a language agnostic manner simply from its propagation characteristics. An example is to measure the degree of community polarization around contentious topics, identify the factions involved, and recognize their individual views on issues. The analysis is independent of the language of discourse itself, making it valuable for multilingual media, where the number of languages used may render language-specific analysis less scalable.

Original languageEnglish (US)
Title of host publicationNext-Generation Analyst V
EditorsTimothy P. Hanratty, James Llinas
PublisherSPIE
ISBN (Electronic)9781510609150
DOIs
StatePublished - Jan 1 2017
Event5th Conference on Next-Generation Analyst - Anaheim, United States
Duration: Apr 10 2017Apr 11 2017

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10207
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

Other5th Conference on Next-Generation Analyst
CountryUnited States
CityAnaheim
Period4/10/174/11/17

Fingerprint

information flow
Information Flow
Social Networks
Polarization
Propagation
propagation
Social Media
Algorithm Analysis
relay
Relay
Language
polarization

Keywords

  • Social networks
  • signal processing

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Roy, H., Abdelzaher, T., Bowman, E. K., & Al Amin, M. T. (2017). Information flow on social networks: From empirical data to situation understanding. In T. P. Hanratty, & J. Llinas (Eds.), Next-Generation Analyst V [1020702] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 10207). SPIE. https://doi.org/10.1117/12.2266585

Information flow on social networks : From empirical data to situation understanding. / Roy, Heather; Abdelzaher, Tarek; Bowman, Elizabeth K.; Al Amin, Md Tanvir.

Next-Generation Analyst V. ed. / Timothy P. Hanratty; James Llinas. SPIE, 2017. 1020702 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 10207).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Roy, H, Abdelzaher, T, Bowman, EK & Al Amin, MT 2017, Information flow on social networks: From empirical data to situation understanding. in TP Hanratty & J Llinas (eds), Next-Generation Analyst V., 1020702, Proceedings of SPIE - The International Society for Optical Engineering, vol. 10207, SPIE, 5th Conference on Next-Generation Analyst, Anaheim, United States, 4/10/17. https://doi.org/10.1117/12.2266585
Roy H, Abdelzaher T, Bowman EK, Al Amin MT. Information flow on social networks: From empirical data to situation understanding. In Hanratty TP, Llinas J, editors, Next-Generation Analyst V. SPIE. 2017. 1020702. (Proceedings of SPIE - The International Society for Optical Engineering). https://doi.org/10.1117/12.2266585
Roy, Heather ; Abdelzaher, Tarek ; Bowman, Elizabeth K. ; Al Amin, Md Tanvir. / Information flow on social networks : From empirical data to situation understanding. Next-Generation Analyst V. editor / Timothy P. Hanratty ; James Llinas. SPIE, 2017. (Proceedings of SPIE - The International Society for Optical Engineering).
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