UAE Researchers Gauge Social Media Sentiment on Metaverse Adoption
Summary:
A group of UAE researchers carried out a study to gauge public sentiments about the metaverse on social media platform, X. Using machine learning, they categorized 86,565 posts into positive (53%), neutral (33%) and negative (14%) sentiments. The model deployed by the team achieved 92.6% accuracy, marking a significant improvement over prior investigations. The findings suggest positivity for metaverse adoption. However, discussions not mentioning 'metaverse' were not considered, marking a limitation of the study. Future research aims to incorporate more social media platforms and traditional sentiment analysis techniques for a more comprehensive review.
A group of specialists from the United Arab Emirates have recently conducted an investigation in order to gauge public opinions about the metaverse as expressed on social media platforms. The team compiled a dataset comprising 86,565 contributions from users on X, previously known as Twitter, assigning them to either positive, negative or neutral sentiment-based categories through the use of machine learning technology. Based on their findings, the majority of the posts, 45,506 or 53%, expressed a positive outlook on the metaverse. Neutral views made up 33% with 28,663 posts, while the remaining 14% or 12,396 posts expressed a negative sentiment. An instance of a positive post mentioned in their study was along the lines of expressing enthusiasm for developing the metaverse, while a negative post example questioned the desirability of the metaverse compared to real-life interaction. In their study, the researchers noted that both positive and negative sentiments tended to follow certain patterns, but the neutral posts showed no discernable pattern. The results suggest that the metaverse technology has potential for widespread adoption. Hayawi, et. al., 2024 is cited as the source of the image. Prior investigations that utilized machine learning to discern public sentiment about the metaverse through social media posts have achieved about 88% precision — implying that more than a 10th of the posts may be incorrectly classified or misunderstood by the algorithms. The models deployed by the team from the U.A.E achieved accuracy levels up to 92.6% across a dataset of over 85K posts, establishing this study as an incredibly thorough analysis of public sentiment about the metaverse. However, the research is not yet peer-reviewed. Further research will incorporate other social media platforms such as Meta and Reddit, and will make use of traditional sentiment analysis techniques like scientific surveys for a more holistic view. The researchers concede that the current study has limitations, as it only considered posts containing the keyword "metaverse". Thus, relevant discussions not directly mentioning this word were excluded from this study.
Published At
3/7/2024 8:20:49 PM
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