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Investigation of the effects of YouTube videos about orthognathic surgery on people using machine learning-based emotion analysis algorithm
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Objectives:
This study aims to analyze the comments about orthognathic surgery-themed YouTube videos through artificial intelligence and remarking the emotional effects of videos on people.
Material and Methods:
In this study, the keyword “orthognathic surgery” was searched on YouTube. In pursuit of recording sub-video comments, comments were analyzed with a machine learning-based emotion analysis algorithm.
Results:
One thousand one hundred and forty-five comments were analyzed in the study. 2 of 4 surgery videos contain real surgery images. Two videos are animated videos about the details of the surgery. Emotions described in comments are sorted as fear (43.7%), joy (21%), anger (14.6%), and sadness (11.6%). Where comments are reviewed in the aspect of sentiment, negative comments were dense (59.3%), respectively, followed by positive (18.3%), very negative (10.6%), and very positive (2.7 %). Regarding sentiment, differences in comments on real and animation surgery videos are statistically significant (
P
< 0.05). A significance level of very negative comments was higher in real surgery videos (
P
= 0.015).
Conclusion:
Different video formats, animation or real videos, may be used for informing, but we think that watching real surgical operation videos may increase people’s preoperative anxiety.
Title: Investigation of the effects of YouTube videos about orthognathic surgery on people using machine learning-based emotion analysis algorithm
Description:
Objectives:
This study aims to analyze the comments about orthognathic surgery-themed YouTube videos through artificial intelligence and remarking the emotional effects of videos on people.
Material and Methods:
In this study, the keyword “orthognathic surgery” was searched on YouTube.
In pursuit of recording sub-video comments, comments were analyzed with a machine learning-based emotion analysis algorithm.
Results:
One thousand one hundred and forty-five comments were analyzed in the study.
2 of 4 surgery videos contain real surgery images.
Two videos are animated videos about the details of the surgery.
Emotions described in comments are sorted as fear (43.
7%), joy (21%), anger (14.
6%), and sadness (11.
6%).
Where comments are reviewed in the aspect of sentiment, negative comments were dense (59.
3%), respectively, followed by positive (18.
3%), very negative (10.
6%), and very positive (2.
7 %).
Regarding sentiment, differences in comments on real and animation surgery videos are statistically significant (
P
< 0.
05).
A significance level of very negative comments was higher in real surgery videos (
P
= 0.
015).
Conclusion:
Different video formats, animation or real videos, may be used for informing, but we think that watching real surgical operation videos may increase people’s preoperative anxiety.
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