TY - JOUR
T1 - Predictive Modeling of Instagram User Engagement with tourist photos based on Visual Attributes
T2 - 3rd International Tourism, Hospitality and Gastronomy Congress, ITHGC 2022
AU - Ciriaco, Samantha
AU - Garayar, Diana
AU - Sotomayor, Sandra
AU - Villalba, Klinge
N1 - Publisher Copyright:
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)
PY - 2022
Y1 - 2022
N2 - In the tourism sector, photography has evolved from capturing memories to be-coming a tourism digital marketing strategy. The goal of this study is to identify the most important visual attributes that increase Instagram Engagement of the tourist destination Taquile Island (Peru). A predictive model that relates visual attributes and Engagement was developed using 439 photos of Taquile Island extracted from Instagram. These attributes were quantified using Image Analy-sis tools. Neural networks were used for the predictive model construction. This research shows that the most important visual attributes to increase the en-gagement on Instagram are lifestyle and natural landscape.
AB - In the tourism sector, photography has evolved from capturing memories to be-coming a tourism digital marketing strategy. The goal of this study is to identify the most important visual attributes that increase Instagram Engagement of the tourist destination Taquile Island (Peru). A predictive model that relates visual attributes and Engagement was developed using 439 photos of Taquile Island extracted from Instagram. These attributes were quantified using Image Analy-sis tools. Neural networks were used for the predictive model construction. This research shows that the most important visual attributes to increase the en-gagement on Instagram are lifestyle and natural landscape.
KW - Predictive model
KW - engagement
KW - neural networks
KW - visual content analysis
KW - visual destination image
UR - http://www.scopus.com/inward/record.url?scp=85147905766&partnerID=8YFLogxK
M3 - Artículo de la conferencia
AN - SCOPUS:85147905766
SN - 1613-0073
VL - 3336
SP - 17
EP - 27
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
Y2 - 27 October 2022 through 28 October 2022
ER -
