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Political Messaging through Language Patterns and Sentiment Analysis in Twitter Messages - Focusing on the US President Twitter
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- 발행기관
- 한국언어연구학회 바로가기
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- 간행물
- 언어학연구 KCI 등재 바로가기
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- 통권
- 제25권 3호 (2020.12)바로가기
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- 페이지
- pp.25-51
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A390393
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6,600원
원문정보
초록
- 영어
- This paper makes a text mining analysis of the US President Donald Trump and the former President Barack Obama’s remarks on their respective Twitter accounts to examine what words are mainly used by these powerful politicians, and through that what political messages they attempt to convey. The study analyzes Twitter messages from 2017 to 2019 in terms of language patterns and sentiment analysis. The analysis of the language patterns is focused on the use of parts of speech, the use of capital letters, and exclamation points. The results show that Trump uses pronouns most and verbs and nouns are followed, while Obama uses nouns most and pronouns and verbs are next. Trump uses capital letters much more than Obama and the most frequently used word is GREAT while Obama hardly uses capital letters. In the case of Trump, he uses exclamation points with the word, you most while the word everybody is the case for Obama. As there is no nonverbal language elements such as intonation in text messages, Trump tends to use many capital letters and exclamation points to express his feelings as nonverbal elements of language. Through sentiment analysis it was found that both politicians use more positive words than negative words. However, Trump uses more negative words than Obama. As the messages on Twitter have become a primary means for political communication, the two politicians tend to use more positive words to create the positive images.
목차
Abstract
1. Introduction
2. Literature Review
2.1 Twitter’s Role in Politics on Social Media Engagement
2.2 Nonverbal Language Elements in Text Based Communication
2.3 Sentiment Analysis in Twitter Messages
3. Methodology
3.1 Data Collection and Classification of Valid Data
3.3 Data Analysis
4. Results and Discussion
4.1 Analysis of Twitter Language Use Patterns
4.2 Analysis of the Use of Capital Letters and Punctuation Points as Linguistic Elements of Twitter Messages
4.3 Sentiment Analysis
5. Conclusion
References
키워드
Twitter messages political messages language patterns sentiment analysis positive words저자
간행물 정보
발행기관
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- 발행기관명
- 한국언어연구학회 [The Korean Association of Language Studies]
- 설립연도
- 1996
- 분야
- 인문학>언어학
- 소개
- 한국언어연구학회는 언어학과 언어교육 분야의 연구를 통하하여 학문의 질적 향상과 국내외 회원 및 학회간의 학술 교류와 친목을 도모한다. 이를 위해 학술 연구 발표회, 강연회, 강습회를 개최하고, 정기학회지, 연구보고서, 서적 등을 간행하며, 그 밖에 지역사회에 필요한 사업과 연구 활동을 수행하는데 중점을 두고 있다.
간행물
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- 간행물명
- 언어학연구 [Journal of Linguistic Studies]
- 간기
- 연3회
- pISSN
- 1226-9859
- 수록기간
- 1996~2025
- 등재여부
- KCI 등재
- 십진분류
- KDC 700 DDC 400
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