TY - CHAP
T1 - User Comments as a Resource to Rank with Multiple Criteria
T2 - The Case of TripAdvisor Athens’s Restaurants
AU - Novas, Dimitris
AU - Papakyriakopoulos, Dimitris
AU - Kartaloglou, Elissavet
AU - Griva, Anastasia
N1 - Publisher Copyright:
© 2023, Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - User-generated content is used to evaluate products and services and tourism industry has been one of the most influenced, due to the existence of vast amount of user-generated data, which is an important resource to foster ranking mechanisms. Though, almost all the online travel platforms (e.g., TripAdvisor, Yelp, Expedia) do not reveal enough details regarding how they valuate/rank hotels, flights, restaurants, etc. The objective of this work is to propose a preliminary ranking mechanism, which relies on the qualitative characteristics of the comments by incorporating Latent Dirichlet Allocation and multi-criteria decision-making. We empirically study the ranking mechanism using TripAdvisor’s user comments on restaurants located in Athens, Greece. The results are evaluated using a simple quantitative ranking scheme and we conclude by considering the theoretical contributions and practical implications and further developments of the proposed ranking approach.
AB - User-generated content is used to evaluate products and services and tourism industry has been one of the most influenced, due to the existence of vast amount of user-generated data, which is an important resource to foster ranking mechanisms. Though, almost all the online travel platforms (e.g., TripAdvisor, Yelp, Expedia) do not reveal enough details regarding how they valuate/rank hotels, flights, restaurants, etc. The objective of this work is to propose a preliminary ranking mechanism, which relies on the qualitative characteristics of the comments by incorporating Latent Dirichlet Allocation and multi-criteria decision-making. We empirically study the ranking mechanism using TripAdvisor’s user comments on restaurants located in Athens, Greece. The results are evaluated using a simple quantitative ranking scheme and we conclude by considering the theoretical contributions and practical implications and further developments of the proposed ranking approach.
KW - Fuzzy numbers
KW - Multi-criteria analysis
KW - Ranking
KW - Restaurants
KW - Text mining
KW - TripAdvisor
UR - https://www.scopus.com/pages/publications/85171167475
U2 - 10.1007/978-3-031-34892-1_8
DO - 10.1007/978-3-031-34892-1_8
M3 - Chapter
AN - SCOPUS:85171167475
T3 - Multiple Criteria Decision Making
SP - 145
EP - 170
BT - Multiple Criteria Decision Making
PB - Springer Science and Business Media Deutschland GmbH
ER -