Investigating the Relevant Agro Food Keyword in Malaysian Online Newspapers

Mohamad Farhan Mohamad Mohsin, Siti Sakira Kamaruddin, Fadzilah Siraj, Hamirul Aini Hambali, Mohammed Ahmed Taiye


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.


agro-food keywords; news mining; RAKE algorithm; text mining; online newspaper.

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