쟁점 사안에 대한 핵심 어휘 판별 및 시각화를 통한 언론사별 논조 분석Analyzing the Tone of Each Press by Identifying and Visualizing Core Words on Issues
- Other Titles
- Analyzing the Tone of Each Press by Identifying and Visualizing Core Words on Issues
- Authors
- 최종현; 강필성
- Issue Date
- 2020
- Publisher
- 한국경영과학회
- Keywords
- Cred TF-IDF; Scaled F-Score; Attention Mechanism; Text-Mining
- Citation
- 한국경영과학회지, v.45, no.4, pp.1 - 10
- Indexed
- KCI
- Journal Title
- 한국경영과학회지
- Volume
- 45
- Number
- 4
- Start Page
- 1
- End Page
- 10
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/131136
- ISSN
- 1225-1119
- Abstract
- Media outlets regularly publish articles on the same issue using various tones that are distinct to each media company. To discover how one company’s tone is different from those of other outlets is presented in news articles, we designed a text analytics framework based on the weight scores of words used in politics and editorial sections from four major domestic newspaper companies. In our experiment, we selected five controversial political issues and collected related newspaper articles reported within a specified period. Then, we preprocessed these articles, such as tokenizing and part-of-speech tagging, an open-source Korean morpheme analyzer. The weights of the words are computed on the basis of the frequency-based CRED TF-IDF and scaled F-score. In addition, we constructed a neural network classifier to categorize the publisher of each article correctly on the basis of an attention mechanism to find highly contributive words for publisher discrimination. Lastly, we analyzed the differences in tones by visualizing keywords to provide an intuitive understanding.
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Collections - College of Engineering > School of Industrial and Management Engineering > 1. Journal Articles
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