Liao Shiting, Wang Yunpei, Wang Qingnian
School of Journalism and Communication, South China University of Technology, Guangzhou, Guangdong, China.
School of Economics and Management, South China Normal University, Guangzhou, Guangdong, China.
PeerJ Comput Sci. 2024 Oct 9;10:e2376. doi: 10.7717/peerj-cs.2376. eCollection 2024.
In the digital media age, international news commentary has changed, creating challenges such as information overload and noise. Traditional platforms often need more data-driven analysis capabilities. This study presented a specialized intelligent system for processing international news commentary data. The system provided robust analysis tools, automated recommendations, and summarization capabilities. Its comprehensive modules included data crawling, processing, visualization, and retrieval. Experimental results demonstrated the system's effectiveness in processing data and generating valuable insights. Users were able to gain objective insights into topics, emotions, and dissemination patterns. The system provided valuable resources for communication research, enhancing theoretical understanding and practical applications in the field.
在数字媒体时代,国际新闻评论发生了变化,带来了信息过载和噪音等挑战。传统平台往往缺乏数据驱动的分析能力。本研究提出了一种用于处理国际新闻评论数据的专门智能系统。该系统提供了强大的分析工具、自动推荐和总结功能。其综合模块包括数据爬取、处理、可视化和检索。实验结果证明了该系统在处理数据和生成有价值见解方面的有效性。用户能够对主题、情感和传播模式获得客观的见解。该系统为传播研究提供了有价值的资源,增强了该领域的理论理解和实际应用。