Authors :
Amirthanathan Prashanthan; Maneesha Rajapaksha; Binuri Thilakarathna
Volume/Issue :
Volume 8 - 2023, Issue 8 - August
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
http://tinyurl.com/4ed8634a
DOI :
https://doi.org/10.5281/zenodo.8318940
Abstract :
In the context of swiftly progressing
technological advances, Virtual Reality (VR) and
Augmented Reality (AR) emerge as crucial developments
with the potential to profoundly transform education,
work environments, and society at large. This research
article provides a thorough examination of the attitudes
expressed by individuals towards VR and AR technology,
as well as their corresponding experiences and views. The
research used a custom sentiment analysis model that was
trained using a dataset consisting of 107 responses
obtained from a survey that was specifically created to
investigate the various factors which influence the
integration of AR and VR in daily life. Additionally, the
survey aimed to measure the sentiments associated with
these immersive technologies. The study utilizes machine
learning techniques to identify subtle emotional nuances
present in written responses. The sentiment analysis
model is carefully constructed using a rigorous training
method to assess each response and categorize sentiments
into positive, negative, or neutral classifications. The
factors that exert a significant influence on the
integration of AR and VR technologies include the
educational advantages, collaborative efforts in the
workplace, and cost considerations. Furthermore,
through the examination of sentiment predictions, this
study reveals the range of emotions linked to the
incorporation of VR and AR technologies into
educational and professional environments.
Keywords :
Augmented, Model, Machine Learning, Predictions.
In the context of swiftly progressing
technological advances, Virtual Reality (VR) and
Augmented Reality (AR) emerge as crucial developments
with the potential to profoundly transform education,
work environments, and society at large. This research
article provides a thorough examination of the attitudes
expressed by individuals towards VR and AR technology,
as well as their corresponding experiences and views. The
research used a custom sentiment analysis model that was
trained using a dataset consisting of 107 responses
obtained from a survey that was specifically created to
investigate the various factors which influence the
integration of AR and VR in daily life. Additionally, the
survey aimed to measure the sentiments associated with
these immersive technologies. The study utilizes machine
learning techniques to identify subtle emotional nuances
present in written responses. The sentiment analysis
model is carefully constructed using a rigorous training
method to assess each response and categorize sentiments
into positive, negative, or neutral classifications. The
factors that exert a significant influence on the
integration of AR and VR technologies include the
educational advantages, collaborative efforts in the
workplace, and cost considerations. Furthermore,
through the examination of sentiment predictions, this
study reveals the range of emotions linked to the
incorporation of VR and AR technologies into
educational and professional environments.
Keywords :
Augmented, Model, Machine Learning, Predictions.
