Predictive Modeling of Instagram User Engagement with tourist photos based on Visual Attributes: The case of Taquile Island - Peru

Samantha Ciriaco; Diana Garayar; Sandra Sotomayor; Klinge Villalba

Predictive Modeling of Instagram User Engagement with tourist photos based on Visual Attributes: The case of Taquile Island - Peru

Samantha Ciriaco, Diana Garayar, Sandra Sotomayor, Klinge Villalba

Universidad San Ignacio de Loyola

Research output: Contribution to journal › Conference article › peer-review

Abstract

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.

Original language	English
Pages (from-to)	17-27
Number of pages	11
Journal	CEUR Workshop Proceedings
Volume	3336
State	Published - 2022
Externally published	Yes
Event	3rd International Tourism, Hospitality and Gastronomy Congress, ITHGC 2022 - Lima, Peru Duration: 27 Oct 2022 → 28 Oct 2022

Keywords

Predictive model
engagement
neural networks
visual content analysis
visual destination image

Cite this

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title = "Predictive Modeling of Instagram User Engagement with tourist photos based on Visual Attributes: The case of Taquile Island - Peru",

abstract = "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.",

keywords = "Predictive model, engagement, neural networks, visual content analysis, visual destination image",

author = "Samantha Ciriaco and Diana Garayar and Sandra Sotomayor and Klinge Villalba",

note = "Publisher Copyright: {\textcopyright} 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0); 3rd International Tourism, Hospitality and Gastronomy Congress, ITHGC 2022 ; Conference date: 27-10-2022 Through 28-10-2022",

year = "2022",

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journal = "CEUR Workshop Proceedings",

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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

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

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M3 - Conference article

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 -

Predictive Modeling of Instagram User Engagement with tourist photos based on Visual Attributes: The case of Taquile Island - Peru

Abstract

Keywords

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