Online news veracity assessment using emotional weight

Fatin Amanina Ahmad Tarmizi, Tan Phan Xuan, Khaironi Yatim Sharif, Eiji Kamioka

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

Abstract

Trillions of data are being created every day on the Internet due to the growing number of social platforms on the World Wide Web (WWW). Processed data when given in context makes information of any knowledge. However, irresponsible use of the data or misinterpretation of data could be the reasons for false information dissemination. Many researchers from various fields, such as computer science and social science, draw their focus on assessing the veracity of information. There are many techniques to perceive this topic, for instance, social network behaviour, and semantic analysis. The common practice is using semantic analysis approach, where the syntactic structure is analysed and polarity of the texts is determined. In this paper, we approach the veracity assessment by using emotion analysis. We identified emotional states conveyed in news content and calculated the weight of each state in each news content. Contrary to popular belief, our finding showed that emotional, or affective states conveyed in false news are varied - positive and negative states. The distinct feature is the weight of the states in news content. Using multi-layer perceptron, we classified the news and achieved 90% accuracy with our collected dataset and 85% using LIAR dataset.

Original languageEnglish
Title of host publicationACM International Conference Proceeding Series
PublisherAssociation for Computing Machinery
Pages60-64
Number of pages5
ISBN (Print)9781450361033
DOIs
Publication statusPublished - 2019 Jan 1
Event2nd International Conference on Information Science and System, ICISS 2019 - Tokyo, Japan
Duration: 2019 Mar 162019 Mar 19

Publication series

NameACM International Conference Proceeding Series
VolumePart F148384

Conference

Conference2nd International Conference on Information Science and System, ICISS 2019
CountryJapan
CityTokyo
Period19/3/1619/3/19

Fingerprint

Semantics
Information dissemination
Social sciences
Multilayer neural networks
Syntactics
World Wide Web
Computer science
Internet

Keywords

  • Affective science
  • Deception detection
  • Text analysis, emotion analysis
  • Veracity assessment

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Tarmizi, F. A. A., Phan Xuan, T., Sharif, K. Y., & Kamioka, E. (2019). Online news veracity assessment using emotional weight. In ACM International Conference Proceeding Series (pp. 60-64). (ACM International Conference Proceeding Series; Vol. Part F148384). Association for Computing Machinery. https://doi.org/10.1145/3322645.3322688

Online news veracity assessment using emotional weight. / Tarmizi, Fatin Amanina Ahmad; Phan Xuan, Tan; Sharif, Khaironi Yatim; Kamioka, Eiji.

ACM International Conference Proceeding Series. Association for Computing Machinery, 2019. p. 60-64 (ACM International Conference Proceeding Series; Vol. Part F148384).

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

Tarmizi, FAA, Phan Xuan, T, Sharif, KY & Kamioka, E 2019, Online news veracity assessment using emotional weight. in ACM International Conference Proceeding Series. ACM International Conference Proceeding Series, vol. Part F148384, Association for Computing Machinery, pp. 60-64, 2nd International Conference on Information Science and System, ICISS 2019, Tokyo, Japan, 19/3/16. https://doi.org/10.1145/3322645.3322688
Tarmizi FAA, Phan Xuan T, Sharif KY, Kamioka E. Online news veracity assessment using emotional weight. In ACM International Conference Proceeding Series. Association for Computing Machinery. 2019. p. 60-64. (ACM International Conference Proceeding Series). https://doi.org/10.1145/3322645.3322688
Tarmizi, Fatin Amanina Ahmad ; Phan Xuan, Tan ; Sharif, Khaironi Yatim ; Kamioka, Eiji. / Online news veracity assessment using emotional weight. ACM International Conference Proceeding Series. Association for Computing Machinery, 2019. pp. 60-64 (ACM International Conference Proceeding Series).
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