A social influence model for exploring double subjectivity through news frames in online news

Loretta H. Cheeks, Ashraf Gaffar

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

Abstract

The Internet is the premier platform for the proliferation of news. Online news is unstructured narrative text that embeds facts, frames, and bias that can influence society about critical issues. Online news sources are carriers of news that operate within complex and dynamic networks. The informational flows, interactions, and structural variations of online news lead to asymmetries and influence societal attitudes and beliefs. Current efforts to express the internal embeddedness in online news text are limited by the use of existing computational tools. This research has the potential to inform advanced machine learning and to help researchers to understand implicit structural embeddedness to address real-world critical issues. This paper establishes the new concept of double subjectivity, proposes a formal definition of a news frame issues network, and introduces a social influence model for the discovery of distinct pathways. The paper also exposes opinion shifts in complex networks for future computational treatment of narrative text.

Original languageEnglish (US)
Title of host publication2017 Intelligent Systems Conference, IntelliSys 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages23-33
Number of pages11
Volume2018-January
ISBN (Electronic)9781509064359
DOIs
StatePublished - Mar 23 2018
Event2017 Intelligent Systems Conference, IntelliSys 2017 - London, United Kingdom
Duration: Sep 7 2017Sep 8 2017

Other

Other2017 Intelligent Systems Conference, IntelliSys 2017
CountryUnited Kingdom
CityLondon
Period9/7/179/8/17

Fingerprint

Social Influence
Flow interactions
Complex networks
Learning systems
Internet
Complex Networks
Dynamic Networks
Proliferation
Model
Asymmetry
Pathway
Machine Learning
Express
Internal
Distinct
Interaction
Text
Influence
Narrative

Keywords

  • Artificial intelligence
  • bias
  • data mining
  • framing
  • machine learning
  • natural language processing
  • news source sentiment
  • sentiment analysis
  • social influence
  • subjectivity

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Optimization

Cite this

Cheeks, L. H., & Gaffar, A. (2018). A social influence model for exploring double subjectivity through news frames in online news. In 2017 Intelligent Systems Conference, IntelliSys 2017 (Vol. 2018-January, pp. 23-33). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IntelliSys.2017.8324285

A social influence model for exploring double subjectivity through news frames in online news. / Cheeks, Loretta H.; Gaffar, Ashraf.

2017 Intelligent Systems Conference, IntelliSys 2017. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 23-33.

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

Cheeks, LH & Gaffar, A 2018, A social influence model for exploring double subjectivity through news frames in online news. in 2017 Intelligent Systems Conference, IntelliSys 2017. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 23-33, 2017 Intelligent Systems Conference, IntelliSys 2017, London, United Kingdom, 9/7/17. https://doi.org/10.1109/IntelliSys.2017.8324285
Cheeks LH, Gaffar A. A social influence model for exploring double subjectivity through news frames in online news. In 2017 Intelligent Systems Conference, IntelliSys 2017. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 23-33 https://doi.org/10.1109/IntelliSys.2017.8324285
Cheeks, Loretta H. ; Gaffar, Ashraf. / A social influence model for exploring double subjectivity through news frames in online news. 2017 Intelligent Systems Conference, IntelliSys 2017. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 23-33
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