
doi: 10.4108/eetsis.3843
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.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
