Discursive representations of immigration in The New York Times: Integrating computational and pragmatic approaches

• 발행기관: 경희대학교 언어정보연구소
• 저자명: Seongmin Mun Hye-Kyung Lee
• 간행물 정보: 『언어연구』제43권 제2호, 621~646쪽, 전체 26쪽
• 주제분류: 인문학 > 언어학
• 파일형태: PDF
• 발행일자: 2026.06.30

국문 초록

This study investigates how immigrants are represented in The New York Times by applying text mining techniques and critical discourse analysis to a corpus of 1,000 immigration-related news articles. Combining methods such as word frequency analysis, word embeddings, and clustering, the study identifies major thematic domains within immigration discourse, including political and legal processes, border control, socio-economic impacts, and urban life. The analysis reveals that while overtly negative terms are largely absent, linguistic choices frequently foreground immigrants’ legal status, framing them in ways that implicitly reinforce institutional ideologies and marginalization. The study further argues that such delicate ideological representations often elude large-scale quantitative approaches, highlighting the limitations of automated, frequency-based text analysis. The absence of explicitly negative language is attributed to both methodological constraints and data bias, including sampling limitations and a narrow source base. As such, the findings emphasize the need for “smart big data”, datasets that combine volume with contextual richness, and call for the integration of qualitative discourse analysis to reflect the pragmatic and ideological complexity of media language. By connecting computational and interpretive approaches, this research contributes to interdisciplinary scholarship on critical discourse analysis, immigration studies, and data methodologies.

목차

1. Introduction

2. Literature review

3. Data and methodology

4. Results and discussion

5. Discussion: Qualitative analysis

6. Conclusion

References

키워드

immigration discourse media representation critical discourse analysis text mining smart big data

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