DOI : https://doi.org/10.18517/ijaseit.9.6.7955

Investigating the Relevant Agro Food Keyword in Malaysian Online Newspapers

Mohamad Farhan Mohamad Mohsin (1), Siti Sakira Kamaruddin (2), Fadzilah Siraj (3), Hamirul Aini Hambali (4), Mohammed Ahmed Taiye (5)
(1) School of Computing, College of Arts & Sciences, Universiti Utara Malaysia, Kedah, Malaysia
(2) School of Computing, College of Arts & Sciences, Universiti Utara Malaysia, Kedah, Malaysia
(3) School of Computing, College of Arts & Sciences, Universiti Utara Malaysia, Kedah, Malaysia
(4) School of Computing, College of Arts & Sciences, Universiti Utara Malaysia, Kedah, Malaysia
(5) School of Computing, College of Arts & Sciences, Universiti Utara Malaysia, Kedah, Malaysia
Fulltext View | Download
How to cite (IJASEIT) :
Mohamad Mohsin, Mohamad Farhan, et al. “Investigating the Relevant Agro Food Keyword in Malaysian Online Newspapers”. International Journal on Advanced Science, Engineering and Information Technology, vol. 9, no. 6, Dec. 2019, pp. 2166-75, doi:10.18517/ijaseit.9.6.7955.
Citation Format :
Online newspaper is a valuable resource of information for decision making. To extract relevant information from them is a challenging process when their volume is massive, and its knowledge is in an unstructured form that is scattered on every page.  This situation becomes more complicated when different news providers have different styles of journalism when reporting a similar event and use different concepts and terms.  In this study, we examined the three Malaysian English online newspapers in order to identify knowledge in terms of the most relevant keywords used in daily online news. The news articles related to Agro-food industries were taken from online news websites - The Star Online, The Sun Daily, and The News Straits Times. During the extraction, about 458 Agro-food industries news articles were scrapped from the website within the time frame of 2014-2017.  The keywords were extracted using the RAKE algorithm and were classified into 4 groups i.e. agriculture, livestock, fishery and miscellaneous. The agriculture keywords group was found as the most frequent keywords in all newspapers (58%) and it was followed by the livestock (23%), fishery (12%), and miscellaneous (7%). Through the analysis, there were 146 Agro-related keywords found in all newspapers, repeated 720 times, and the highest Agro terms were found in The Star Online (35.13%), followed by The Sun Daily (33.78%), and The News Straits Times (31.08%). There were 12 Agro keywords0 which considered as the most relevant when they appear in all newspapers- palm oil, rice, fruits, fish, vegetable, livestock, paddy, crop, chicken, animal, meat, and beef. The ‘palm oil’ is the most popular keyword among the three newspapers and it was found 37 times (38.9%) in The Star Online, 26 times (37.9%) in News Straits Time, and repeated 22 times (23.2%) in the Sun. The identified keywords can be recommended as input to form a future Agro inventory.

S. Steve, “"Plato People” Reunite, Honor Founder,” Culture, 1997. [Online]. Available: https://www.wired.com/1997/03/platopeople-reunite-honor-founder/. [Accessed: 28-Jun-2018].

A. Taylor, The People’s Platform: Taking Back Power and Culture in the Digital Age. 2014.

R. í˜. Ní¸rvËšag, Kjetil, “News Item Extraction for Text Mining inWeb Newspapers,” in International Workshop on Challenges in Web Information Retrieval and Integration, 2005.

M. S. and R. W. A Yzaguirre, “Newspaper archives + text mining = rich sources of historical geo-spatial data,” IOP Conf. Ser. Earth Environ. Sci. 34, vol. 34, pp. 1-8, 2016.

D. O. Tony Harcup, “WHAT IS NEWS?” Journal. Stud., vol. 18,no. 12, pp. 1470-1488, 2017.

S. Carina, Ihlstrí¶m Eriksson, í…kesson, Maria Nordqvist, “From Print to Web to e-paper - the challenge of designing the e- newspaper,” in International Council for Computer Communication (ICCC), 2004, pp. 249-260.

J. Edwards, “For every £154 newspapers lose in print revenue, they gain only £5 on the digital side,” Business Insider UK, 2017. [Online]. Available: http://uk.businessinsider.com/statistics- smartphones-print-newspaper-revenues-2017-2/?IR=T. [Accessed: 09-Jul-2018].

EBizMBA, “Top 15 Most Popular News Websites,” eBizMBAInc, 2018. [Online]. Available: http://www.ebizmba.com/articles/ newswebsites.

Malaysia Central, “Malaysian News: List Of Online Media, Newspapers, Dailies, Print Versions, News Portals, Independent Media, Alternative Press & News Agencies, News Sources & Publications,” MALAYSIA CENTRAL: The Leading Malaysia- Centric Info Portal, 2016. [Online]. Available: http://www.mycen.com.my/malaysia/news.html. [Accessed: 18- Jul-2018].

G. S. L. Vishal Gupta, “A Survey of Text Mining Techniques and Applications,” J. Emerg. Technol. Web Intell., vol. 1, no. 1, pp.60-79, 2009.

J. Z. Xiangyu Tang, Chunyu Yang, “Stock Price Forecasting by Combining News Mining and Time Series Analysis,” in ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2009, pp. 1-5.

S. Pollak, R. Coesemans, W. Daelemans, and N. LavraÄ, “Detecting contrast patterns in newspaper articles by combining discourse analysis and text mining,” Pragmatics. Q. Publ. Int. Pragmat. Assoc., vol. 21, no. 4, pp. 647-683, 2011.

S. M. A. Aqil M. Azmi, “Aara’- a system for mining the polarity of Saudi public opinion through e-newspaper comments,” J. Inf. Sci., vol. 40, no. 3, 2014.

S. P. and N. A. R. Mazidah Puteh, Norulhidayah Isa, “Sentiment Mining of Malay Newspaper (SAMNews) Using Artificial Immune System,” in Proceedings of the World Congress on Engineering, 2013, pp. 1-6.

O. R. L. S. ZhongmingMa, GautamPant, “Mining competitor relationships from online news: A network-based approach,” Electron. Commer. Res. Appl., vol. 10, no. 4, pp. 418-427, 2011.

J. Yoon, “Detecting weak signals for long-term business opportunities using text mining of Web news,” Expert Syst. Appl., vol. 39, no. 16, pp. 12543-12550, 2012.

E. D. Goodman, “Agro” Food Studies in the ‘Age of Ecology’: Nature, Corporeality, Bio” Politics,” J. Eur. Soc. Rural Sociol., vol. 39, no. 1, pp. 17-38, 1999.

S. R. D. E. N. C. W. Cowley, “Automatic Keyword Extraction from Individual Documents,” in Text Mining: Applications and Theory, M. W. B. Kogan, Ed. John Wiley & Sons, Ltd, 2010, pp. 1-120.

Vidya, S., & Banumathy, K. (2015). Web Mining-Concepts and Applications. International Journal of Computer Science and Information Technologies, 6(4), 3266-3268.

Mughal, M. J. H. (2018). Data Mining: Web Data Mining Techniques, Tools and Algorithms: An Overview. International Journal of Advanced Computer Science and Applications, 9(6).

Mebrahtu, A., & Srinivasulu, B. (2017). Web Content Mining Techniques and Tools. International Journal of Computer Science and Mobile Computing, 6(4).

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
    2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
    3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).