Representation of linguistic characteristics in mass media
Bibliographic Data
| ID | 22140346 |
|---|---|
| Authors | Hasan Busri (Universitas Islam Malang), Moh Badrih (Universitas Islam Malang) |
| Year | 2022 |
| Volume | 8 |
| Issue | 1 |
| Pages | 1-14 |
| Publication date | 2022-04-14 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | KEMBARA Journal of Scientific Language Literature and Teaching (JOURNAL) |
| Journal identifiers | ISSN: 2442-9287 • E-ISSN: 2442-9287 |
| Publisher | Universitas Muhammadiyah Malang (PUBLISHER) |
| DOI | 10.22219/kembara.v8i1.19324 |
| OpenAlex | W4401008827 |
| Language | EN |
| Citations received | 7 |
| References cited | 8 |
The language characteristics of the mass media have always been a reference for the actuality of the news and the awesomeness of the events covered by journalists. The characteristics of the language sometimes refer to the events being covered, but not a few of the language's rhetoric goes beyond the events reported. Therefore, the characteristics of the language and the rhetorical style become the representation of journalists in reporting an event. In journalistic studies, representation is interpreted as one of the journalists' strategies to present events in a news text. So, in this study, three very relevant issues are raised: (1) how is vocabulary represented, (2) how is grammatical representation, and (3) how is local coherence represented in newspaper news texts. This study aims to explain the meaning and mode contained in local vocabulary, grammar, and coherence. Based on the problems and objectives, the method used in this research is the phenomenological method. The phenomenological method is used to find out the events behind phenomena or texts written by journalists. Analysis of the data in this study uses descriptive discourse analysis and critical discourse analysis. The data sources for this research are the printed mass media of Kompas, Jawa Pos (regional), and Surya (regional) newspapers which are taken randomly from May to October 2021. The collection techniques include focused observation, theoretical and logical triangulation, as well as rolling/snowball patterns. The researcher is the key instrument in this study and uses four companion instruments: data codification, descriptive analysis guide, explanatory analysis guide, and data corpus table. The research data analysis model is an adaptation of the flow analysis model and the type of interactive analysis, including the reduction, assessment, and inference (verification) stages of withdrawal. The findings in this research are (1) Vocabulary representation, including associations and metaphors. Associations are used by journalists to create an atmosphere in news texts so that they can be precarious, soft, serious, and tasteless. Metaphors are used by journalists to show journalists' attitudes and judgments towards an object in the text; (2) Grammatical representation, including (a) the form of the process: action process, event process, state process, and mental process; (b) participants include: participants as perpetrators, participants as victims, and participants as nominal; and (c) Representation of a combination of clauses or local coherence, including elaboration, additional extension, contrast extension, choice extension, and augmentation extension. In conclusion, in the newspaper news text, there are vocabulary representations in the form of associations and metaphors, grammatical representation in the form of process and readiness, and local coherence in the form of elaboration, expansion, an extension of contrast, an extension of choice, and extension of heightening
Critical discourse analysis · Grammar · Linguistics · Mass media · Media studies · Newspaper · Political science · Rhetorical question · Sociology · Vocabulary · Computer Science · Education and Communication Studies · English Language Learning and Teaching · Linguistics and Language Analysis · Mathematics
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| Unique citing works | 7 |
|---|---|
| Citations per year | 1.75 |
| Citation span | 2022 - 2024 (3) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 4 |