Discourse Semantics: Analysis on Appraisal System for reader’s comment section in Jakarta Globe Online Newspaper

ABSTRACT

This study focuses to investigate the appraisal systems in the reader’s comments of Jakarta Globe online newspaper. The reader’s comment in the online newspaper demonstrates the linguistics phenomena on how the commenter evaluates the posted article. The commentators might express their feeling, evaluate the behaviour, and appreciate a thing in composing the comments.

A descriptive qualitative research design is conducted as some reasons. First, this research examines the readers’ comments which are in the form of words. The data are collected from www.JakartaGlobe.com. Second, the researcher is the main instrument in collecting and analysing the data. Third, this research is aimed at describing Appraisal systems analysis on the Jakarta Globe readers’ comments and seeing how the commenters describe attitude and other appraisal systems.

By applying “Appraisal theory” propounded by Martin & White (2005), the findings denotes the use of attitude systems; positive affect-attitude (1, 19%), negative affect-attitude (3, 61%), positive judgement-attitude (13, 09%), negative judgement-attitude (59, 52%), positive appreciation-attitude (8, 33%), negative appreciation-attitude (14,28%). The negative judgement seems to dominate the attitude system. It indicates that the commenter often compose the comment by evaluating the behaviour. Furthermore, the analysis of graduation system explicates intensification-force-graduation (30, 95%), quantification-force- graduation (64, 28%), softening-focus-graduation (0%), sharpening-focus- graduation (4, 72%). The highest percentage of force graduation may implies that the high frequency of using the intensification and quantification in grading the system of meaning. Also, the engagement analysis shows the different percentage among the systems; monoglossia (41, 83%), proclaim-heteroglossia (3, 06%), disclaim-heteroglossia (26, 53%), entertain-heteroglossia (19, 39%), attribute- heteroglossia (9, 18%). The highest percentage of monoglossia system instead the others systems demonstrate the high frequency used of not acknowledging the external voice in the comment.