@article{oai:kitami-it.repo.nii.ac.jp:02000441,
 author = {Victor Silaa and Fumito Masui and Michal Ptaszynski},
 issue = {5},
 journal = {Applied Sciences},
 month = {2023-07-21},
 note = {When planning a travel or an adventure, sightseers increasingly rely on opinions posted on
the Internet tourism related websites, such as TripAdvisor, Booking.com or Expedia. Unfortunately,
beautiful, yet less-known places and rarely visited sightspots often do not accumulate sufficient
number of valuable opinions on such websites. On the other hand, users often post their opinions
on casual social media services, such as Facebook, Instagram or Twitter. Therefore, in this study, we
develop a system for supplementing insufficient number of Internet opinions available for sightspots
with tweets containing opinions of such sightspots, with a specific focus on wildlife sightspots. To
do that, we develop an approach consisting of a system (PSRS) for wildlife sightspots and propose
a method for verifying collected geotagged tweets and using them as on-spot reviews. Tweets
that contain geolocation information are considered geotagged and therefore treated as possible
tourist on-spot reviews. The main challenge, however, is to confirm the authenticity of the extracted
tweets. Our method includes the use of location clustering and classification techniques. Specifically,
extracted geotagged tweets are clustered by using location information and then annotated taking
into consideration specific features applied to machine learning-based classification techniques. As
for the machine learning (ML) algorithms, we adopt a fine-tuned transformer neural network-based
BERT model which implements the information of token context orientation. The BERT model
achieved a higher F-score of 0.936, suggesting that applying a state-of-the-art deep learning-based
approach had a significant impact on solving this task. The extracted tweets and annotated scores are
then mapped on the designed Park Supplementary Review System (PSRS) as supplementary reviews
for travelers seeking additional information about the related sightseeing spots.},
 pages = {2321--2321},
 title = {A Method of Supplementing Reviews to Less-Known Tourist Spots Using Geotagged Tweets},
 volume = {12},
 year = {}
}