Abstract
To evaluate credibility of Arabic content in Twitter, a corpus of Arabic microblogging messages was required with its labelled credibility ratings in order to build the credibility model. Since no Arabic dataset existed, we confronted this problem by building a novel human annotated Arabic Twitter corpus that could be used for further research. This paper identifies the collection process and the characteristics of the newly created dataset. It presents basic analysis of submitted credibility rating values and the collected labelers’ data. A number of statistical graphs are exhibited to examine labelers’ traits and its impact on credibility perceptions. Results showed that both: labelers’ data and method of labeling presentation have a slight impact on the perception of credibility. The results presented in this paper covers the first stage from a large project aims at predicting credibility of Arabic Twitter messages in the presence of disagreed judging credibility scores.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hansen, D., Shneiderman, B., Smith, M.A.: Analyzing Social Media Networks with NodeXL: Insights from a Connected World. Morgan Kaufmann, Burlington (2010)
Kąkol, M., Jankowski-Lorek, M., Abramczuk, K., Wierzbicki, A., Catasta, M.: On the subjectivity and bias of web content credibility evaluations. In: Proceedings of the 22nd International Conference on World Wide Web companion, pp. 1131–1136 (2013)
Flanagin, A.J., Metzger, M.J.: The perceived credibility of personal Web page information as influenced by the sex of the source. Comput. Hum. Behav. 19(6), 683–701 (2003)
Fogg, B.J., Marshall, J., Laraki, O., Osipovich, A., Varma, C., Fang, N., Paul, J., Rangnekar, A., Shon, J., Swani, P., et al.: What makes web sites credible? a report on a large quantitative study. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 61–68 (2001)
Fogg, B.J., Marshall, J., Kameda, T., Solomon, J., Rangnekar, A., Boyd, J., Brown, B.: Web credibility research: a method for online experiments and early study results. In: CHI 2001 Extended Abstracts on Human Factors in Computing Systems, pp. 295–296 (2001)
Goldberg, L.R.: The International Personality Item Pool (IPIP) (1999). Internet site: http://ipip.ori.org/ipip
Rideout, V.J., Foehr, U.G., Roberts, D.F.: Generation M [superscript 2]: Media in the Lives of 8-to 18-Year-Olds. Henry J. Kaiser Family Foundation, Menlo Park (2010)
Hilligoss, B., Rieh, S.Y.: Developing a unifying framework of credibility assessment: construct, heuristics, and interaction in context. Inf. Process. Manag. 44(4), 1467–1484 (2008)
Fogg, B.J.: Prominence-interpretation theory: explaining how people assess credibility online. In: CHI 2003 Extended Abstracts on Human Factors in Computing Systems, pp. 722–723 (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
AlMansour, A.A. (2018). Credibility Perception for Arab Users. In: Bi, Y., Kapoor, S., Bhatia, R. (eds) Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016. IntelliSys 2016. Lecture Notes in Networks and Systems, vol 16. Springer, Cham. https://doi.org/10.1007/978-3-319-56991-8_80
Download citation
DOI: https://doi.org/10.1007/978-3-319-56991-8_80
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-56990-1
Online ISBN: 978-3-319-56991-8
eBook Packages: EngineeringEngineering (R0)