Color and engagement in touristic Instagram pictures: A machine learning approach

J. Yu; R. Egger

doi:10.1016/j.annals.2021.103204

Color and engagement in touristic Instagram pictures: A machine learning approach

J. Yu
, R. Egger

Research output: Contribution to journal › Article › peer-review

Abstract

Color plays a critical role in recognizing tourist experiences and influencing their emotions. By classifying tourism photos on Instagram using machine learning, this study uncovers the relationship between color and user engagement based on pictures with different features. The findings show that the presence of the color blue in photos featuring natural scenery, high-end gastronomy, and sacral architectures contributes to user engagement. A red/orange color scheme enhances pictures regarding local delicacies and ambience, while the coexistence of violet and warm colors is crucial for photographs featuring cityscapes and interior design. By taking a broader lens from aesthetic philosophy and narrowing down to color psychology, this study offers guidelines for marketers to promote tourism activities through the application of color.

Original language	English
Journal	Ann. Tour. Res.
Volume	89
DOIs	https://doi.org/10.1016/j.annals.2021.103204
Publication status	Published - 1 Jul 2021

Keywords

Aesthetics
Color psychology
Engagement
Instagram
Machine learning
Tourism photography
color
esthetics
machine learning
photography
psychology
social media
tourist behavior

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10.1016/j.annals.2021.103204

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104131499&doi=10.1016%2fj.annals.2021.103204&partnerID=40&md5=f2d6beb3466ee0d8385d6bf5636ebb9e

Cite this

@article{e1f3ae973cfc45ed980787f6a251e933,

title = "Color and engagement in touristic Instagram pictures: A machine learning approach",

abstract = "Color plays a critical role in recognizing tourist experiences and influencing their emotions. By classifying tourism photos on Instagram using machine learning, this study uncovers the relationship between color and user engagement based on pictures with different features. The findings show that the presence of the color blue in photos featuring natural scenery, high-end gastronomy, and sacral architectures contributes to user engagement. A red/orange color scheme enhances pictures regarding local delicacies and ambience, while the coexistence of violet and warm colors is crucial for photographs featuring cityscapes and interior design. By taking a broader lens from aesthetic philosophy and narrowing down to color psychology, this study offers guidelines for marketers to promote tourism activities through the application of color.",

keywords = "Aesthetics, Color psychology, Engagement, Instagram, Machine learning, Tourism photography, color, esthetics, machine learning, photography, psychology, social media, tourist behavior",

author = "J. Yu and R. Egger",

note = "Cited By :46 Export Date: 14 December 2023 Correspondence Address: Yu, J.; Department of Innovation and Management in Tourism, Urstein S{\"u}d 1, Austria; email: [email protected] Funding details: Rijksuniversiteit Groningen, RUG Funding text 1: The authors would like to express their appreciation to Ms. Michelle Mattuzzi, a Research Master student in Language and Cognition at the University of Groningen, for proofreading the manuscript. Michelle can be contacted via email on [email protected].☆ This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. References: Ahmad, I., Basheri, M., Iqbal, M., Rahim, A., Performance comparison of support vector machine, random forest, and extreme learning machine for intrusion detection (2018) IEEE Access, 6, pp. 33789-33795; AL-Ayash, A., Kane, R.T., Smith, D., Green-Armytage, P., The influence of color on student emotion, heart rate, and performance in learning environments (2016) Color Research \& Application, 41 (2), pp. 196-205; Aminudin, N., Nazary, M.M., Jamal, S.A., Volunsharing of Lenggong Valley world heritage site: A content analysis (2020) Journal of Tourism, Hospitality \& Culinary Arts, 12 (1), pp. 329-346; Amsteus, M., Al-Shaaban, S., Wallin, E., Sj{\"o}qvist, S., Colors in marketing: A study of color associations and context (in)dependence (2015) International Journal of Business and Social Science, 6 (3), pp. 32-45; Aramendia-Muneta, M.E., Olarte-Pascual, C., (2020), pp. 50-76. , Ollo-L{\'o}pez, A. Key image attributes to elicit likes and comments on Instagram. Journal of Promotion Management; Aslam, M.M., Are you selling the right colour? A cross-cultural review of colour as a marketing cue (2006) Journal of Marketing Communications, 12 (1), pp. 15-30; Arefieva, V., Egger, R., Yu, J., A machine learning approach to cluster destination image on Instagram (2021) Tourism Management, 85, p. 104318; Bakhshi, S., Gilbert, E., Red, purple and pink: The colors of diffusion on pinterest (2015) PLoS One, 10 (2); Balomenou, N., Garrod, B., Georgiadou, A., Making sense of tourists' photographs using canonical variate analysis (2017) Tourism Management, 61, pp. 173-179; Bharadwaj, N., Ballings, M., Naik, P.A., Cross-media consumption: Insights from super bowl advertising (2020) Journal of Interactive Marketing, 50, pp. 17-31; Binnie, J., Does viewing art in the museum reduce anxiety and improve wellbeing? (2010) Museums \& Social Issues, 5 (2), pp. 191-201; Brinck, I., Empathy, engagement, entrainment: The interaction dynamics of aesthetic experience (2018) Cognitive Processing, 19 (2), pp. 201-213; Browet, A., Absil, P.A., Van Dooren, P., Community detection for hierarchical image segmentation (2011) International workshop on combinatorial image analysis, pp. 358-371. , Springer Berlin, Heidelberg; Cyr, D., Head, M., (2010), pp. 1-21. , Larios, H. Colour appeal in website design within and across cultures: A multi-method evaluation. International Journal of Human-Computer Studies, 68(1{\textendash}2); Datta, B., Kaushik, P., Brand awareness through Instagram advertising (2019) Asian Journal of Management, 10 (2), pp. 100-108; Dekimpe, M.G., Retailing and retailing research in the age of big data analytics (2020) International Journal of Research in Marketing, 37 (1), pp. 3-14; Dimson, T., Machine learning @scale - measurement and analysis of prediction (2017), https://fb.watch/3L9Maf243W/; Filieri, R., What makes an online consumer review trustworthy? (2016) Annals of Tourism Research, 58, pp. 46-64; Gao, J., Kerstetter, D.L., From sad to happy to happier: Emotion regulation strategies used during a vacation (2018) Annals of Tourism Research, 69, pp. 1-14; Garaus, M., Halkias, G., One color fits all: Product category color norms and (a)typical package colors (2019) Review of Managerial Science, 26 (1), p. 280; Google Cloud, Detect labels (2020), https://cloud.google.com/vision/docs/labels?hl=zh-tw; He, L., Qi, H., Zaretzki, R., Image color transfer to evoke different emotions based on color combinations (2015) Signal, Image and Video Processing, 9 (8), pp. 1965-1973; Hsieh, Y.C., Chiu, H.C., Tang, Y.C., Lee, M., Do colors change realities in online shopping? (2018) Journal of Interactive Marketing, 41, pp. 14-27; Jaakonm{\"a}ki, R., M{\"u}ller, O., (2017), Vom Brocke, J. The impact of content, context, and creator on user engagement in social media marketing. In Proceedings of the 50th Hawaii international conference on system sciences; Jalali, N.Y., Papatla, P., The palette that stands out: Color compositions of online curated visual UGC that attracts higher consumer interaction (2016) Quantitative Marketing and Economics, 14 (4), pp. 353-384; Jansson, A., Rethinking post-tourism in the age of social media (2018) Annals of Tourism Research, 69, pp. 101-110; Jeong, E., Jang, S., The affective psychological process of self-image congruity and its influences on dining experience (2018) International Journal of Contemporary Hospitality Management, 30 (3), pp. 1563-1583; Joyner, L., Kline, C., Oliver, J., Kariko, D., Exploring emotional response to images used in agritourism destination marketing (2018) Journal of Destination Marketing \& Management, 9, pp. 44-55; Khoja, N., Visual content marketing statistics to know for 2020 (2020), https://venngage.com/blog/visual-content-marketing-statistics/; Kim, H., Stepchenkova, S., Effect of tourist photographs on attitudes towards destination: Manifest and latent content (2015) Tourism Management, 49, pp. 29-41; Kirillova, K., Wassler, P., Travel beautifully: The role of aesthetics in experience design (2019) Atmospheric turn in culture and tourism: Place, design and process impacts on customer behaviour, marketing and branding, , Emerald Publishing Limited; Kirillova, K., Fu, X., Lehto, X., Cai, L., What makes a destination beautiful? Dimensions of tourist aesthetic judgment (2014) Tourism Management, 42, pp. 282-293; Kuhzady, S., Ghasemi, V., Pictorial analysis of the projected destination image: Portugal on Instagram (2019) Tourism Analysis, 24 (1), pp. 43-54; Labrecque, L.I., Milne, G.R., Exciting red and competent blue: The importance of color in marketing (2012) Journal of the Academy of Marketing Science, 40 (5), pp. 711-727; Labrecque, L.I., Patrick, V.M., Milne, G.R., The marketers{\textquoteright} prismatic palette: A review of color research and future directions (2013) Psychology \& Marketing, 30 (2), pp. 187-202; Landis, J.R., Koch, G.G., The measurement of observer agreement for categorical data (1977) Biometrics, 33 (1), pp. 159-174; Lee, A.H., What does colour tell about tourist experiences? (2020) Tourism geographies, pp. 1-22; Li, Y., Xie, Y., Is a picture worth a thousand words? An empirical study of image content and social media engagement (2020) Journal of Marketing Research, 57 (1), pp. 1-19; Liang, S., Li, C., Zhang, X., Li, H., The snowball effect in online travel platforms: How does peer influence affect review posting decisions? (2020) Annals of Tourism Research, 85; Lin, H.C., Swarna, H., Bruning, P.F., Taking a global view on brand post popularity: Six social media brand post practices for global markets (2017) Business Horizons, 60 (5), pp. 621-633; Lund, N.F., Cohen, S.A., Scarles, C., The power of social media storytelling in destination branding (2018) Journal of Destination Marketing \& Management, 8, pp. 271-280; Ma, S.D., Kirilenko, A.P., Automated identification of tourist activities in social media photographs: A comparative analysis using visual-based, textual-based and joint-based methods (2020) E-review of Tourism Research, 17 (4), pp. 557-570; Martinez-Torres, M.R., Toral, S.L., A machine learning approach for the identification of the deceptive reviews in the hospitality sector using unique attributes and sentiment orientation (2019) Tourism Management, 75, pp. 393-403; Mata, I.L., Fossgard, K., Haukeland, J.V., Do visitors gaze and reproduce what destination managers wish to commercialise? Perceived and projected image in the UNESCO World Heritage area (2018) International Journal of Digital Culture and Electronic Tourism, 2 (4), pp. 294-321; Matikiti-Manyevere, R., Kruger, M., The role of social media sites in trip planning and destination decision-making processes (2019) African Journal of Hospitality, Tourism and Leisure, 8 (5), pp. 1-10; Mazanec, J.A., Hidden theorizing in big data analytics: With a reference to tourism design research (2020) Annals of Tourism Research, 83; Narangajavana, Y., Fiol, L.J.C., Tena, M.{\'A}.M., Artola, R.M.R., Garc{\'i}a, J.S., The influence of social media in creating expectations. An empirical study for a tourist destination (2017) Annals of Tourism Research, 65, pp. 60-70; Nguyen, T.K., Coustaty, M., (2018), Guillaume, J.L. A new image segmentation approach based on the Louvain algorithm. In 2018 international conference on content-based multimedia indexing (pp. 1{\textendash}6). 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Differences in user-generated images (Instagram), official tourist brochures and travel guides (2018) Annals of Tourism Research, 73, pp. 103-115; Phillips, J., Holcomb, E.J., Kelley, K., Determining interest in value-added planters: Consumer preference and current grower and retailer perceptions (2007) HortTechnology, 17 (2), pp. 238-246; Picazo, P., Moreno-Gil, S., Analysis of the projected image of tourism destinations on photographs: A literature review to prepare for the future (2019) Journal of Vacation Marketing, 25 (1), pp. 3-24; Poels, K., Dewitte, S., The role of emotions in advertising: A call to action (2019) Journal of Advertising, 48 (1), pp. 81-90; Rama, Z., (2018), Han, H. The value creation in brand public. [Unpublished master thesis]. 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year = "2021",

month = jul,

day = "1",

doi = "10.1016/j.annals.2021.103204",

language = "English",

volume = "89",

journal = "Ann. Tour. Res.",

issn = "0160-7383",

publisher = "Elsevier Ltd",

}

TY - JOUR

T1 - Color and engagement in touristic Instagram pictures: A machine learning approach

AU - Yu, J.

AU - Egger, R.

N1 - Cited By :46 Export Date: 14 December 2023 Correspondence Address: Yu, J.; Department of Innovation and Management in Tourism, Urstein Süd 1, Austria; email: [email protected] Funding details: Rijksuniversiteit Groningen, RUG Funding text 1: The authors would like to express their appreciation to Ms. Michelle Mattuzzi, a Research Master student in Language and Cognition at the University of Groningen, for proofreading the manuscript. Michelle can be contacted via email on [email protected].☆ This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. References: Ahmad, I., Basheri, M., Iqbal, M., Rahim, A., Performance comparison of support vector machine, random forest, and extreme learning machine for intrusion detection (2018) IEEE Access, 6, pp. 33789-33795; AL-Ayash, A., Kane, R.T., Smith, D., Green-Armytage, P., The influence of color on student emotion, heart rate, and performance in learning environments (2016) Color Research & Application, 41 (2), pp. 196-205; Aminudin, N., Nazary, M.M., Jamal, S.A., Volunsharing of Lenggong Valley world heritage site: A content analysis (2020) Journal of Tourism, Hospitality & Culinary Arts, 12 (1), pp. 329-346; Amsteus, M., Al-Shaaban, S., Wallin, E., Sjöqvist, S., Colors in marketing: A study of color associations and context (in)dependence (2015) International Journal of Business and Social Science, 6 (3), pp. 32-45; Aramendia-Muneta, M.E., Olarte-Pascual, C., (2020), pp. 50-76. , Ollo-López, A. Key image attributes to elicit likes and comments on Instagram. Journal of Promotion Management; Aslam, M.M., Are you selling the right colour? A cross-cultural review of colour as a marketing cue (2006) Journal of Marketing Communications, 12 (1), pp. 15-30; Arefieva, V., Egger, R., Yu, J., A machine learning approach to cluster destination image on Instagram (2021) Tourism Management, 85, p. 104318; Bakhshi, S., Gilbert, E., Red, purple and pink: The colors of diffusion on pinterest (2015) PLoS One, 10 (2); Balomenou, N., Garrod, B., Georgiadou, A., Making sense of tourists' photographs using canonical variate analysis (2017) Tourism Management, 61, pp. 173-179; Bharadwaj, N., Ballings, M., Naik, P.A., Cross-media consumption: Insights from super bowl advertising (2020) Journal of Interactive Marketing, 50, pp. 17-31; Binnie, J., Does viewing art in the museum reduce anxiety and improve wellbeing? (2010) Museums & Social Issues, 5 (2), pp. 191-201; Brinck, I., Empathy, engagement, entrainment: The interaction dynamics of aesthetic experience (2018) Cognitive Processing, 19 (2), pp. 201-213; Browet, A., Absil, P.A., Van Dooren, P., Community detection for hierarchical image segmentation (2011) International workshop on combinatorial image analysis, pp. 358-371. , Springer Berlin, Heidelberg; Cyr, D., Head, M., (2010), pp. 1-21. , Larios, H. Colour appeal in website design within and across cultures: A multi-method evaluation. International Journal of Human-Computer Studies, 68(1–2); Datta, B., Kaushik, P., Brand awareness through Instagram advertising (2019) Asian Journal of Management, 10 (2), pp. 100-108; Dekimpe, M.G., Retailing and retailing research in the age of big data analytics (2020) International Journal of Research in Marketing, 37 (1), pp. 3-14; Dimson, T., Machine learning @scale - measurement and analysis of prediction (2017), https://fb.watch/3L9Maf243W/; Filieri, R., What makes an online consumer review trustworthy? (2016) Annals of Tourism Research, 58, pp. 46-64; Gao, J., Kerstetter, D.L., From sad to happy to happier: Emotion regulation strategies used during a vacation (2018) Annals of Tourism Research, 69, pp. 1-14; Garaus, M., Halkias, G., One color fits all: Product category color norms and (a)typical package colors (2019) Review of Managerial Science, 26 (1), p. 280; Google Cloud, Detect labels (2020), https://cloud.google.com/vision/docs/labels?hl=zh-tw; He, L., Qi, H., Zaretzki, R., Image color transfer to evoke different emotions based on color combinations (2015) Signal, Image and Video Processing, 9 (8), pp. 1965-1973; Hsieh, Y.C., Chiu, H.C., Tang, Y.C., Lee, M., Do colors change realities in online shopping? (2018) Journal of Interactive Marketing, 41, pp. 14-27; Jaakonmäki, R., Müller, O., (2017), Vom Brocke, J. The impact of content, context, and creator on user engagement in social media marketing. In Proceedings of the 50th Hawaii international conference on system sciences; Jalali, N.Y., Papatla, P., The palette that stands out: Color compositions of online curated visual UGC that attracts higher consumer interaction (2016) Quantitative Marketing and Economics, 14 (4), pp. 353-384; Jansson, A., Rethinking post-tourism in the age of social media (2018) Annals of Tourism Research, 69, pp. 101-110; Jeong, E., Jang, S., The affective psychological process of self-image congruity and its influences on dining experience (2018) International Journal of Contemporary Hospitality Management, 30 (3), pp. 1563-1583; Joyner, L., Kline, C., Oliver, J., Kariko, D., Exploring emotional response to images used in agritourism destination marketing (2018) Journal of Destination Marketing & Management, 9, pp. 44-55; Khoja, N., Visual content marketing statistics to know for 2020 (2020), https://venngage.com/blog/visual-content-marketing-statistics/; Kim, H., Stepchenkova, S., Effect of tourist photographs on attitudes towards destination: Manifest and latent content (2015) Tourism Management, 49, pp. 29-41; Kirillova, K., Wassler, P., Travel beautifully: The role of aesthetics in experience design (2019) Atmospheric turn in culture and tourism: Place, design and process impacts on customer behaviour, marketing and branding, , Emerald Publishing Limited; Kirillova, K., Fu, X., Lehto, X., Cai, L., What makes a destination beautiful? Dimensions of tourist aesthetic judgment (2014) Tourism Management, 42, pp. 282-293; Kuhzady, S., Ghasemi, V., Pictorial analysis of the projected destination image: Portugal on Instagram (2019) Tourism Analysis, 24 (1), pp. 43-54; Labrecque, L.I., Milne, G.R., Exciting red and competent blue: The importance of color in marketing (2012) Journal of the Academy of Marketing Science, 40 (5), pp. 711-727; Labrecque, L.I., Patrick, V.M., Milne, G.R., The marketers’ prismatic palette: A review of color research and future directions (2013) Psychology & Marketing, 30 (2), pp. 187-202; Landis, J.R., Koch, G.G., The measurement of observer agreement for categorical data (1977) Biometrics, 33 (1), pp. 159-174; Lee, A.H., What does colour tell about tourist experiences? (2020) Tourism geographies, pp. 1-22; Li, Y., Xie, Y., Is a picture worth a thousand words? An empirical study of image content and social media engagement (2020) Journal of Marketing Research, 57 (1), pp. 1-19; Liang, S., Li, C., Zhang, X., Li, H., The snowball effect in online travel platforms: How does peer influence affect review posting decisions? (2020) Annals of Tourism Research, 85; Lin, H.C., Swarna, H., Bruning, P.F., Taking a global view on brand post popularity: Six social media brand post practices for global markets (2017) Business Horizons, 60 (5), pp. 621-633; Lund, N.F., Cohen, S.A., Scarles, C., The power of social media storytelling in destination branding (2018) Journal of Destination Marketing & Management, 8, pp. 271-280; Ma, S.D., Kirilenko, A.P., Automated identification of tourist activities in social media photographs: A comparative analysis using visual-based, textual-based and joint-based methods (2020) E-review of Tourism Research, 17 (4), pp. 557-570; Martinez-Torres, M.R., Toral, S.L., A machine learning approach for the identification of the deceptive reviews in the hospitality sector using unique attributes and sentiment orientation (2019) Tourism Management, 75, pp. 393-403; Mata, I.L., Fossgard, K., Haukeland, J.V., Do visitors gaze and reproduce what destination managers wish to commercialise? Perceived and projected image in the UNESCO World Heritage area (2018) International Journal of Digital Culture and Electronic Tourism, 2 (4), pp. 294-321; Matikiti-Manyevere, R., Kruger, M., The role of social media sites in trip planning and destination decision-making processes (2019) African Journal of Hospitality, Tourism and Leisure, 8 (5), pp. 1-10; Mazanec, J.A., Hidden theorizing in big data analytics: With a reference to tourism design research (2020) Annals of Tourism Research, 83; Narangajavana, Y., Fiol, L.J.C., Tena, M.Á.M., Artola, R.M.R., García, J.S., The influence of social media in creating expectations. An empirical study for a tourist destination (2017) Annals of Tourism Research, 65, pp. 60-70; Nguyen, T.K., Coustaty, M., (2018), Guillaume, J.L. A new image segmentation approach based on the Louvain algorithm. In 2018 international conference on content-based multimedia indexing (pp. 1–6). IEEE; Ozkul, E., Boz, H., Bilgili, B., Koc, E., What colour and light do in service atmospherics: A neuro-marketing perspective (2019) Atmospheric turn in culture and tourism: Place, design and process impacts on customer behaviour, marketing and branding, , Emerald Publishing Limited; Pastorella, F., Giacovelli, G., Meo, I.D., Paletto, A., People's preferences for Alpine forest landscapes: Results of an internet-based survey (2017) Journal of Forest Research, 22 (1), pp. 36-43; Paül i Agustí, D., Characterizing the location of tourist images in cities. 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PY - 2021/7/1

Y1 - 2021/7/1

N2 - Color plays a critical role in recognizing tourist experiences and influencing their emotions. By classifying tourism photos on Instagram using machine learning, this study uncovers the relationship between color and user engagement based on pictures with different features. The findings show that the presence of the color blue in photos featuring natural scenery, high-end gastronomy, and sacral architectures contributes to user engagement. A red/orange color scheme enhances pictures regarding local delicacies and ambience, while the coexistence of violet and warm colors is crucial for photographs featuring cityscapes and interior design. By taking a broader lens from aesthetic philosophy and narrowing down to color psychology, this study offers guidelines for marketers to promote tourism activities through the application of color.

AB - Color plays a critical role in recognizing tourist experiences and influencing their emotions. By classifying tourism photos on Instagram using machine learning, this study uncovers the relationship between color and user engagement based on pictures with different features. The findings show that the presence of the color blue in photos featuring natural scenery, high-end gastronomy, and sacral architectures contributes to user engagement. A red/orange color scheme enhances pictures regarding local delicacies and ambience, while the coexistence of violet and warm colors is crucial for photographs featuring cityscapes and interior design. By taking a broader lens from aesthetic philosophy and narrowing down to color psychology, this study offers guidelines for marketers to promote tourism activities through the application of color.

KW - Aesthetics

KW - Color psychology

KW - Engagement

KW - Instagram

KW - Machine learning

KW - Tourism photography

KW - color

KW - esthetics

KW - machine learning

KW - photography

KW - psychology

KW - social media

KW - tourist behavior

UR - https://www.mendeley.com/catalogue/b3a414c4-0c82-36eb-92a4-c58b2e351ae1/

U2 - 10.1016/j.annals.2021.103204

DO - 10.1016/j.annals.2021.103204

M3 - Article

SN - 0160-7383

VL - 89

JO - Ann. Tour. Res.

JF - Ann. Tour. Res.

ER -

Color and engagement in touristic Instagram pictures: A machine learning approach

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