Abstract
In learning narrative literature, students find difficulty in comprehending and approaching the ideological messages beyond the usage of recurrent lexical items in literary narrative texts. This problem comes as a result of the huge number of lexical items literary texts, particularly the narrative, abound in. The use of the computer and of computational linguistics work makes it possible to process and examine large data for a variety of purposes and to investigate questions that could not feasibly be answered if the analysis was carried manually. This paper, therefore, investigates the relevance of using concordance to decode the ideological weight of lexis in narrative literature. The main objective of the paper is to explore the extent to which certain ideologies and themes are decoded in literary narrative texts undergone a computational concordance analysis. This is conducted by means of a computational concordancing that is intended for providing two verifiable inputs: Frequency Distribution (FD) and Key Word in Context (KWIC). The paper is grounded on an experimental study, where 39 majoring English students attending one novel course at Prince Sattam bin Abdulaziz University, were voluntarily involved in an optional course addressing the study of a narrative literary text: Animal Farm. Participants were divided into two groups: an experimental group and a control group. The former was allowed to use concordance, whereas the latter was only permitted to use conventional methods of studying narrative texts (mere reading). Both groups are assigned to find out the themes and the ideological meanings inferred from a selected list of 13 words from the novel. Results show that the experimental group manages, by applying concordance, to decode the ideological weight of the selected words in a more accurate, credible and faster way than the control group. This in turn facilitates the process of determining the intended message addressed in the novel, either at the character-character level of discourse or at the author-readers one.