Comments Analysis on Social Media: A Review

Abstract

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.

Identification of Perceived Challenges in the Green Energy Transition by Turkish Society through Sentiment Analysis

“…In comparison to surveys, social media appears to be a more suitable source for a better and more comprehensive understanding of public perception. This is because surveys tend to represent the perspective of a small group of individuals rather than capturing the overall public opinion or societal views [37]. Additionally, due to the time and high capital costs involved in the data collection process for surveys, the quantity of data is often limited.…”

“…Instagram data are rarely used in studies, both due to API usage requirements and privacy policies. When examining 115 studies related to sentiment and content analysis published between 2010 and 2022, it is observed that only 30 of these studies are related to sentiment analysis, and a total of 36 studies used YouTube comments [37]. In our study, data were collected from YouTube due to the abundance of technical comments, the absence of character limits, and the ease of accessing past data related to the topic.…”