Abstract
Nowadays, the broadcasting of news via social media networks is almost provided in a textual format. The nature of the broadcasted text is considered as unstructured text. Text mining techniques play an essential role in converting the unstructured text into informative knowledge. It has been observed that there is no research has addressed the textual analysis of Arabic newspapers on social media. Accordingly, this paper attempts to bridge this gap through building on related studies and applying various text mining techniques on a new under-researched context. 62,327 posts were collected from 24 Arab Gulf newspapers pages on Facebook. Results indicated that most of the discussed issues in the Arab Gulf region newspapers are related to trade, petroleum, and development. In addition, results revealed that the United Arab of Emirates (UAE) newspapers represent the source that is highly discussing issues regarding trade and economy followed by the Kingdom of Saudi Arabia (KSA) newspapers. Furthermore, results indicated that the financial and health-care issues news in the Arab Gulf region were highly tackled by Alkhaleej (UAE) newspaper. Besides, results pointed out that KSA newspapers, is on the top in disseminating issues regarding education.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Akilan, A.: Text mining: challenges and future directions. In: 2015 2nd International Conference on Electronics and Communication Systems (ICECS), pp. 1679–1684. IEEE, February 2015
Al Emran, M., Shaalan, K.: A survey of intelligent language tutoring systems. In: 2014 International Conference on Advances in Computing, Communications and Informatics, ICACCI, pp. 393–399. IEEE, September 2014
Al-Emran, M., Zaza, S., Shaalan, K.: Parsing modern standard Arabic using treebank resources. In: 2015 International Conference on Information and Communication Technology Research (ICTRC), pp. 80–83. IEEE, May 2015
Al-Kabi, M., Al-Qudah, N.M., Alsmadi, I., Dabour, M., Wahsheh, H.: Arabic/English sentiment analysis: an empirical study. In: The Fourth International Conference on Information and Communication Systems (ICICS 2013), pp. 23–25, April 2013
Atia, S., Shaalan, K.: Increasing the accuracy of opinion mining in Arabic. In: 2015 First International Conference on Arabic Computational Linguistics (ACLing), pp. 106–113. IEEE, April 2015
Cheng, Q., Lu, X., Liu, Z., Huang, J.: Mining research trends with anomaly detection models: the case of social computing research. Scientometrics 103(2), 453–469 (2015)
Collier, N.: Uncovering text mining: a survey of current work on web-based epidemic intelligence. Global Public Health 7(7), 731–749 (2012)
Davalos, S., Merchant, A., Rose, G.M., Lessley, B.J., Teredesai, A.M.: ‘The good old days’: an examination of nostalgia in Facebook posts. Int. J. Hum Comput Stud. 83, 83–93 (2015)
Feldman, R., Dagan, I.: Knowledge discovery in textual databases (KDT). In: KDD, vol. 95, pp. 112–117, August 1995
Hassani, H., Huang, X., Silva, E.S., Ghodsi, M.: A review of data mining applications in crime. Stat. Anal. Data Mining ASA Data Sci. J. 9(3), 139–154 (2016)
Huang, A.: Similarity measures for text document clustering. In: Proceedings of the Sixth New Zealand Computer Science Research Student Conference (NZCSRSC2008), Christchurch, New Zealand, pp. 49–56, April 2008
Injadat, M., Salo, F., Nassif, A.B.: Data mining techniques in social media: a survey. Neurocomputing 214, 654–670 (2016)
Jayashankar, S., Sridaran, R.: Superlative model using word cloud for short answers evaluation in eLearning. Education and Information Technologies, pp. 1–20 (2016)
Kaur, R., Singh, S.: A survey of data mining and social network analysis based anomaly detection techniques. Egyptian Inf. J. 17(2), 199–216 (2016)
Mhamdi, C.: Transgressing media boundaries: news creation and dissemination in a globalized world. Mediterr J. Soc. Sci. 7(5), 272 (2016)
Mhamdi, C.: Framing “the Other” in Times of Conflicts: CNN’s Coverage of the 2003 Iraq War. Mediterr. J. Soc. Sci. 8(2), 147 (2017)
Mizoguchi, R., Giunchiglia, F.: The Semantic Web–ASWC 2006: First Asian Semantic Web Conference, Beijing, China, 3–7 September 2006, Proceedings, vol. 4185. Springer (2006)
Mosley Jr., R.C.: Social media analytics: data mining applied to insurance Twitter posts. In: Casualty Actuarial Society E-Forum, vol. 2, p. 1 (2012)
Nettleton, D.F.: Data mining of social networks represented as graphs. Comput. Sci. Rev. 7, 1–34 (2013)
Nguyen, H.L., Woon, Y.K., Ng, W.K.: A survey on data stream clustering and classification. Knowl. Inf. Syst. 45(3), 535–569 (2015)
Salloum, S.A., Al-Emran, M., Shaalan, K.: A survey of lexical functional grammar in the Arabic context. Int. J. Comput. Netw. Technol. 4(3), 141–147 (2016)
Salloum, S.A., Al-Emran, M., Shaalan, K.: Mining social media text: extracting knowledge from Facebook. Int. J. Comput. Digital Syst. 6(2), 73–81 (2017)
Salloum, S.A., Al-Emran, M., Monem, A.A., Shaalan, K.: A survey of text mining in social media: Facebook and Twitter perspectives. Adv. Sci. Technol. Eng. Syst. J. 2(1), 127–133 (2017b)
Singh, A.: Mining of Social Media data of University students. Education and Information Technologies, pp. 1–12 (2016)
Thomas, E.H., Galambos, N.: What satisfies students? Mining student-opinion data with regression and decision tree analysis. Res. High. Educ. 45(3), 251–269 (2004)
Xu, J.: Joint visual and textual mining on social media. In: 2014 IEEE International Conference on Data Mining Workshop (ICDMW), pp. 1189–1190. IEEE, December 2014
Zaza, S., Al-Emran, M.: Mining and exploration of credit cards data in UAE. In: 2015 Fifth International Conference on e-Learning (econf), pp. 275–279. IEEE, October 2015
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
Salloum, S.A., Al-Emran, M., Abdallah, S., Shaalan, K. (2018). Analyzing the Arab Gulf Newspapers Using Text Mining Techniques. In: Hassanien, A., Shaalan, K., Gaber, T., Tolba, M. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2017. AISI 2017. Advances in Intelligent Systems and Computing, vol 639. Springer, Cham. https://doi.org/10.1007/978-3-319-64861-3_37
Download citation
DOI: https://doi.org/10.1007/978-3-319-64861-3_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-64860-6
Online ISBN: 978-3-319-64861-3
eBook Packages: EngineeringEngineering (R0)