范围(计算机科学)
社会化媒体
数据科学
领域(数学分析)
订单(交换)
内容分析
政府(语言学)
情绪分析
计算机科学
公共领域
万维网
社会科学
社会学
地理
人工智能
业务
数学分析
语言学
哲学
数学
考古
财务
程序设计语言
作者
Brian Alafwan,Manahan Siallagan,Utomo Sarjono Putro
摘要
As the number of people using and participating in social media grows, academics become interest in studying this new media, specifically comment analysis, in order to comprehend public opinion and user behavior. However, there are no studies that map the development of comment analysis domain, which would be valuable for future research. To address the issue, we examine prior publications using PRISMA approach, and offer suggestions for further research. An investigation was conducted to locate pertinent publications published in databases between 2010 and 2022. On the basis of our examination of 115 relevant articles, we found that, within the scope of methodology, prior researches employ two methods (sentiment and content analysis) and three tools (human, software, and mixed coders), and the majority of them concentrate on gathering data from western countries, covering numerous platforms and topics. Based on these findings, we recommend that future research in comment analysis should synthesize methods and instruments. In addition, examine areas that have not been fully explore in terms of platforms (e.g., Instagram and Tiktok), topic (e.g., local government), and regions (e.g., eastern countries) that would be valuable in order to enhance the body of knowledge in this domain.
科研通智能强力驱动
Strongly Powered by AbleSci AI