뉴스기사 빅데이터의 키워드분석을 활용한 창업 트렌드 분석:2013~2022

Analysis entrepreneurship trends using keyword analysis of news article Big Data :2013~2022

초록

This research aims to identify startup trends by analyzing a large number of news articles through semantic network analysis. Using the BIGKinds article analysis service provided by the Korea Press Foundation, 330,628 news articles from 19 newspapers from January 2013 to December 2022 were comprehensively analyzed. The study focused on exploring the changes in key issues over the past decade, considering the impact of the social environment and global economic trends on entrepreneurship. We compared the number of news articles and changes in issues before and after the COVID-19 pandemic, and visualized entrepreneurship trends through frequency analysis, relationship analysis, and correlation analysis. The results of the study showed that the top keywords for entrepreneurship-related words are startup activation and commercialization, and the correlation between COVID-19 and entrepreneurship keywords is almost negligible in a linear sense, but the number of news articles decreased during the pandemic, which has an impact. In particular, the most frequently mentioned keywords are Ministry of SMEs and Startups, place is the United States, and person is limited. The agency was the SBA, and the entrepreneurship sector is more affected by social issues than any other sector, with the important characteristics of increased frequency of prompt access. This study supplies essential basic data for understanding and exploring issues and events related to entrepreneurship and suggests future research topics in the field.

키워드

Big Data; news article; entrepreneurship; COVID-19; trend analysis
제목
뉴스기사 빅데이터의 키워드분석을 활용한 창업 트렌드 분석:2013~2022
제목 (타언어)
Analysis entrepreneurship trends using keyword analysis of news article Big Data :2013~2022
저자
김재억; 전병훈
DOI
10.23023/JPT.2023.11.3.083
발행일
2023-06
저널명
Journal of Platform Technology
권
11
호
3
페이지
83 ~ 97