Towards A Headline-based Deception Detection Approach for Data Veracity in Online Digital News

Authors

  • Normala Che Eembi @ Jamil Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia
  • Iskandar Ishak Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia
  • Fatimah Sidi Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia
  • Lilly Suriani Affendey Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia

Keywords:

Headlines, Deception, Online News, Framework,

Abstract

Since its existence in 1990's, online news has been the major source of news content for news readers. Unfortunately, based on a number of findings, readers tend to judge on certain event based on the news headlines rather than its contents. With the advancement of mobile and web technologies, it is easier to spread news to others and this unhealthy habits can cause negative impacts towards individuals, organizations or nations that are victimized by the news. This paper proposes a framework to detect deceptive online news based on the news headlines. By having an accurate detection upon deceptive news based on its content, it can assist readers to identify misleading news and to help them to find relevant news for their source of information.

References

Y. R. Tausczik and J. W. Pennebaker, “The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods,” J. Lang. Soc. Psychol., vol. 29, no. 1, pp. 24–54, 2010.

V. L. Rubin and T. Vashchilko, “Extending information quality assessment methodology: A new veracity/deception dimension and its measures,” Proc. Am. Soc. Inf. Sci. Technol., vol. 49, no. 1, pp. 1–6, 2012.

T. Lukoianova and V. L. Rubin, “Veracity roadmap: Is big data objective, truthful and credible?,” Adv. Classif. Res. Online, vol. 24, pp. 4–15, 2013.

M. G. Moghaddam and A. Mustapha, “A Temporal-Focused Trustworthiness to Enhance Trust-based Recommender Systems 20J 3 J 3th International Conference on Intelligent Systems Design and Applications ( ISDA ),” pp. 219–223, 2013.

H. Zhang, Z. Fan, J. Zheng, and Q. Liu, “An improving deception detection method in Computer-Mediated Communication,” J. Networks, vol. 7, no. 11, pp. 1811–1816, 2012.

L. Berti-Equille, “Data veracity estimation with ensembling truth discovery methods,” pp. 2628–2636, 2015.

T. Ekin, F. Leva, F. Ruggeri, and R. Soyer, “Application of bayesian methods in detection of healthcare fraud,” Chem. Eng. Trans., vol. 33, pp. 151–156, 2013.

D. Dor, “On newspaper headlines as relevance optimizers,” J. Pragmat., vol. 35, no. 5, pp. 695–721, 2003.

R. Ecker, U.K, Lewandowsky, S., Chang, E.P., Pillai, “The Effects of Subtle Misinformation in News Headlines,” Uma ética para quantos?, vol. XXXIII, no. 2, pp. 81–87, 2014.

D. Q. Wang, “Madness in the Media : Understanding How People With Lived Experience Interpret Newspaper Headlines,” no. April, 2016.

“Most Read Online Newspapers in the World: Mail Online, New York Times and The Guardian - comScore, Inc.” [Online]. Available: https://www.comscore.com/Insights/Data-Mine/Most-Read-Online-Newspapers-in-the-World-Mail-Online-New-York-Times-and-The-Guardian. [Accessed: 24-Jan-2017].

C. E. Osgood, “Where Do Sentences Come From?,” Semant. Interdiscip. Read. Philos. Linguist. Psychol., pp. 88–105, 1971.

M. Knapp, R. Hart, and H. Dennis, “An exploration of deception as a communication construct,” Hum. Commun. …, vol. Fall, no. 1, pp. 15–29, 1974.

T. Dirsehan and M. Çelik, “Profiling online consumers according to their experiences with a special focus on social dimension,” Procedia - Soc. Behav. Sci., vol. 24, pp. 401–412, 2011.

M. Kerby and A. Marland, “Media Management in a Small Polity : Political Elites ’ Synchronized Calls to Regional Talk Radio and Attempted Manipulation of Public Opinion Polls,” no. August, 2015.

S. Afroz, M. Brennan, and R. Greenstadt, “Detecting Hoaxes , Frauds , and Deception in Writing Style Online,” pp. 461–475, 2012.

J. Wayman, N. Orlans, Q. Hu, F. Goodman, A. Ulrich, and V. Valencia, “Technology Assessment for the State of the Art Biometrics Excellence Roadmap. Volume 2 (of 3). Face, Iris, Ear, Voice, and Handwriter Recognition,” vol. 2, no. JUNE 1987, 2008.

M. Brennan and R. Greenstadt, “Practical Attacks Against Authorship Recognition Techniques,” Artif. Intell., pp. 60–65, 2009.

M. G. Frank, M. A. Menasco, and M. O’Sullivan, “Human behavior and deception detection,” Wiley Handb. Sci. Technol. Homel. Secur., 2008.

H. M. Jung, “Information Manipulation Through the Media,” J. Media Econ., vol. 22, no. 4, pp. 188–210, 2009.

O. Hasan, B. Habegger, L. Brunie, N. Bennani, and E. Damiani, “A discussion of privacy challenges in user profiling with big data techniques: The EEXCESS use case,” Proc. - 2013 IEEE Int. Congr. Big Data, BigData 2013, no. 1, pp. 25–30, 2013.

W. W. Guo and M. Looi, “A framework of trust-energy balanced procedure for cluster head selection in ireless sensor networks,” J. Networks, vol. 7, no. 10, pp. 1592–1599, 2012.

J.-W. van Dam and M. van de Velden, “Online profiling and clustering of Facebook users,” Decis. Support Syst., vol. 70, pp. 60–72, 2015.

G. . Xu, Y. . Zhang, and X. . Zhou, “Towards user profiling for web recommendation,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 3809 LNAI, pp. 415–424, 2005.

R. Nielsen and R. Sambrook, “What is Happening to TelevisionNews?,” Digit. news Proj. Reuters Inst., 2016.

S. Meraji and C. Tropper, “A Machine Learning Approach for Optimizing,” vol. 3, no. 2, 2010.

K. P. K. Kumar and G. Geethakumari, “Detecting misinformation in online social networks using cognitive psychology,” pp. 1–22, 2014.

V. Pérez-Rosas and R. Mihalcea, “Experiments in Open Domain Deception Detection,” 2013.

Normala, C. Eembi, @ Jamil, I. Bin Ishak, F. Sidi, L. S. Affendey, A. Mamat, N. B. C. E. @ Jamil, I. Bin Ishak, F. Sidi, L. S. Affendey, and A. Mamat, “A Systematic Review on the Profiling of Digital News Portal for Big Data Veracity,” Procedia Comput. Sci., vol. 72, pp. 390–397, 2015.

David Miller, “The age of the fake,” Spin Watch, 2005.

M. Ott, C. Cardie, and J. Hancock, “Estimating the prevalence of deception in online review communities,” Proc. 21st Int. Conf. World Wide Web - WWW ’12, pp. 201–210, 2012.

S. Rajkumar, “Assortment of Uncertainty and Randomness with Fuzzy logic in deception detection for employee database management system using hotchpotch techniques,” World Appl. Sci. J., vol. 21, no. 6, pp. 854–857, 2013.

R. Mihalcea, C. Science, and C. Science, “Cross-cultural Deception Detection,” pp. 440–445, 2014.

V. Rubin, N. J. Conroy, V. L. Rubin, N. J. Conroy, Y. Chen, and S. Cornwell, “Fake News or Truth ? Using Satirical Cues to Detect Potentially Misleading News Fake News or Truth ? Using Satirical Cues to Detect Potentially Misleading News .,” no. April, 2016.

N. M. Turner, D. G. York, and H. A. Petousis-Harris, “The use and misuse of media headlines: Lessons from the MeNZB??? immunisation campaign,” N. Z. Med. J., vol. 122, no. 1291, pp. 22–27, 2009.

R. A. Metila, “A Discourse Analysis of News Headlines: Diverse Framings for a Hostage-Taking Event,” vol. 2, no. 2, pp. 71–78, 2013.

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Published

2017-09-15

How to Cite

Che Eembi @ Jamil, N., Ishak, I., Sidi, F., & Affendey, L. S. (2017). Towards A Headline-based Deception Detection Approach for Data Veracity in Online Digital News. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2-11), 33–37. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2734