Instagram public and private images as an element for the spatial monitoring of tourist behaviour in cities

Abstract

Purpose

The purpose of this paper is to analyse whether publicly shared images on Instagram are representative of tourist behaviour in a destination. This aspect is crucial for destination image management, as it can influence the way tourists perceive the destination.

Design/methodology/approach

The research compares three different factors: the route followed by a group of tourists, the whole set of photographs taken by them and the images that they made publicly available on Instagram. It relies on a field work done by a group of 122 tourists in Turin (Italy). At a qualitative level, the answers given by tourists to the motivations that led them to share some of the image are analysed.

Findings

The results showed how the spatial distribution of the images shared publicly on Instagram only partially coincides with the whole set of images taken by tourists.

Practical implications

It is important to avoid basing marketing and management policies on just the places featured in publicly shared images. If not, there is a risk of taking decisions based on the behaviour of some, rather than all, tourists.

Originality/value

Many papers claim to be based on the Instagram image as elements to study tourism. However, most of these papers only analyse public images. This fact can affect the results as there may be, for example, areas visited by tourists where photos are not taken. This paper therefore contributes to a better understanding of Instagram as a tool for the study of urban tourism.

Citation

Paül i Agustí, D. (2024), "Instagram public and private images as an element for the spatial monitoring of tourist behaviour in cities", International Journal of Tourism Cities, Vol. 10 No. 3, pp. 1082-1097. https://doi.org/10.1108/IJTC-11-2023-0227

1. Introduction

Photography has become a fundamental element of tourism communication. Traditionally, tourism images were promoted by businesses and destinations. However, nowadays, it is increasingly tourists who promote them. But tourists do not share all their images; they make a selection. This situation can generate idealised images of destinations that, if not met during the tourist visit, can lead to dissatisfaction (Marine-Roig & Ferrer-Rosell, 2018).

An important tool for understanding how tourists receive the destination’s image is Instagram. Instagram has allowed tourists to share their photographs directly, and this has influenced other people’s purchase decisions relating to travel and tourism (Ji, 2021). It has also impacted tourist behaviour at the destination. It has bene shown that those born from 1981 onwards tend to search for local information (about cafes and restaurants) on Instagram when they reach their destinations (Jun, 2022).

The information available on Instagram is rapidly increasing. It has been observed that over 1,000 photos are uploaded onto Instagram every second, with the total number of uploads exceeding in 2021, 50 billion (Li et al., 2023). Analyses based on this volume of data have made it possible to study such phenomena as tourist behaviour over both space and time and the transmission of destination images through image-based content (Paül i Agustí, 2020a, 2020b). Neither should we ignore the fact that the images posted on networks like Instagram can be geolocated; this is something that some users particularly value. In fact, posts that reference specific locations tend to get 79% more engagement (Omnicore, 2022).

There have already been numerous studies of the spatial behaviour of tourists based on Instagram images. It has been noted that Instagram images can be useful for tracking visits, projecting demand, capture visitor flows between different attractions and be used to estimate demand for tourism using spatial econometric models (Kim et al., 2022). Even so, some authors have pointed to the need to improve the way in which the images used in research are analysed, or – at the very least – to find ways of guaranteeing that the data used are representative (Li et al., 2023; Paül i Agustí, 2021; Pickering et al., 2020).

Some authors have even gone as far as noting that before analysing topics such as the content of Instagram images, it is fundamental to know whether these images really represent what interests’ tourists as a whole (Jun, 2022). The main worry here concerns establishing whether or not publicly available images (which have been used in the majority of studies) represent tourists as a whole (or even all of those who post photographs on Instagram). This is, in fact, a field of research that has many shortcomings. In this vein, authors such as Li et al. (2023, p. 9) have underlined that the majority of studies based on Instagram have tended to be “data-dominated without solid theoretical bases”.

This criticism is based on problems that had previously been highlighted by Bauder (2016), who observed that tourists tend to photograph, and most frequently share, images of what they consider meaningful places. This can lead to important differences between the places photographed and those shared. The images made publicly available on Instagram are only part of the total set of images captured by tourists. Based on studies of the spatial behaviour of tourists that only focus on publicly available images may induce errors in the interpretation of results. This is a question that has hitherto received little attention and analysis.

The present research goes beyond the study of photographs shared publicly on Instagram and examines the different degrees of (in)congruence between the whole set of images taken by tourists and those shared on Instagram. It does this via a cartographic analysis that avoids the habitual coarse-grain approach that focuses on an entire destination (Li et al., 2023) and instead examines their heterogeneity and the appeal of smaller units (and of different attractions).

2. Theoretical framework

Although there are other platforms for sharing images online, academic literature typically regards Instagram as the most suitable network for studying visitor behaviour (Tenkanen et al., 2017). However, the use of Instagram also has a series of limitations. The main strengths and weaknesses of using this network as a tool to study tourist behavior are presented below.

2.1 Sharing photographs on Instagram

Photographs are one of the preferred means via which tourists exchange information on social networks, with them mainly doing this to provide proof of having personally visited certain locations (Bauder, 2016). Over 90% of travellers take photos on their journeys, with this helping them to turn memories into narrations and stories (Lo et al., 2011). Although several authors have previously studied images posted on social networks, academic interest in this subject began to grow from around 2015 onwards and particularly after 2020 (Li et al., 2023). Amongst the strong points of such analyses, there is the abundant amount of available visual information and the reliability of the data recorded. Furthermore, Instagram offers an anonymity that makes it possible for users to be honest about what they publish (Jun, 2022).

It is generally agreed that the appearance of social networks has coincided with a redefinition of the tourist gaze (Konijn et al., 2016). First of all, it must be recognised that social networks tend to host companies, organisations and influencers that can influence the publicly projected image of a given destination. That said, it must be added that the images divulged by tourists are not neutral either. In fact, it is common for tourists to manipulate images to make them serve their own particular interests (Jurgenson, 2019).

Tourists sharing images has long been a common practice. Even so, social networks have produced an important leap forward in this practice and one that has brought new challenges to the analysis of shared images (Marine-Roig and Ferrer-Rosell, 2018). Various studies have pointed to a series of sociodemographic characteristics (including nationality, income, education and age) that may influence the online photo-sharing behaviour of different tourists (Li et al., 2023). Others have pointed to environmental stimuli (and the design or quality of the experience) also influencing the number of photographs that are shared (Apaolaza et al., 2021). There is also a tendency for certain people to share more images than others and for tourists to take more photos of themselves than of beauty spots and places of general interest. This is largely due to a desire to transmit a positive self-image via social networks (Dinhopl & Gretzel, 2016). A factor that should also be considered when analysing the different decisions taken by tourists regarding what to photograph and what not to include in their photos.

There is therefore a tendency to find, on the one hand, sets of images that tourists take to capture current moments, which are for their own personal enjoyment and do not necessarily need to represent the truth (Jurgenson, 2019) and, on the other, images that they select to share, and which are much more reflexive and prepared (Jun, 2022). The difference between these two types of behaviour may have an influence on the distribution of the images that tourists share on social networks and, as a result, on any subsequent analysis of such images. Some authors (such as Belk, 2016) have pointed out that the images that people share may accurately reveal certain personality traits, whereas other authors (Garrod, 2008) have observed that they almost inevitably accentuate some subjects rather than others.

Concerning personality traits, research frequently depends on established taxonomies like the Big 5, which organise various characteristics into five categories: experience, conscientiousness, extraversion, agreeableness and neuroticism. Other theories exist, such as the meta-theoretic model of motivation and personality (3M), which explains consumer behaviour on the basis of elemental traits, compound traits, situational traits and surface features (Asebedo et al., 2019). Nevertheless, in tourism and hospitality studies, the Big 5 continues to be the dominant personality theory (Leung & Law, 2010 quoted by Yousaf & Kim, 2023).

The motivations that lead a person to choose one subject inevitably has its own spatial relations and various authors have used images to identify spatio-temporal routes (Kim et al., 2022) and points where tourists tend to concentrate (Paül i Agustí, 2020a; 2020b). Sharing images publicly also has an evidently spatial component and says to everyone: “I’ve been to this place” (Stylianou-Lambert, 2012, p. 1830).

The academic literature has tended to capitalise on the fact that when tourists take photographs, they make choices and immortalise one place but not another. In the same way, when they decide to share images, they favour a series of “significant places” (Urry & Larsen, 2011, p. 179). A behaviour that allows for the hierarchical organisation of tourist space. Bauder (2016), amongst others, observed that tourists can be regarded as part of a “circle of representation” and that they tend to depict space (independently of how it is perceived or the values assigned to it) in terms of the motivations, objects and categories in which they experience it. The places photographed and publicly shared subsequently become “sights”. However, academic literature has tended to primarily work with publicly available photographs. These images can be important (for example, in marketing), but one must not lose sight of the fact that they are only one part of a much wider tourist experience.

2.2 Problems involved with analysing only publicly available photographs

The act of taking a photograph requires a conscious decision concerning a series of elements that to be are included or excluded (Garrod, 2008). A second choice is then made when it comes to posting the resulting image on social networks (Bauder, 2016). This is followed by a third decision as to whether or not to share the image publicly. This set of decisions limits the number of images that are eventually shared publicly (Li et al., 2023). As a result, any study based only on publicly available images may imply an important degree of research bias associated with the nature of the final image, the management of spaces and the final audience (Bui et al., 2022).

It is true that the amount of data available for research has increased enormously. There has also been a significant increase in the number of images that can be computer processed. Metadata can also be used to obtain complementary information that could not be obtained from a simple photograph. However, despite acknowledging this situation authors such as Li et al. (2023, p. 12) have warned that the automated processing of exclusively public images implies potential sources of bias related to their extremity (more positive than negative attitudes) and language. This can affect the representativeness of the data, resulting in the relative overexposure of certain collectives and the under-representation of others.

Several authors have highlighted this amongst the potential limitations of their work. In some cases, they have underlined that only publicly available images have been analysed within relatively simple research criteria and that this may have introduced bias into their samples (Mak, 2017; Tenkanen et al., 2017).

In other cases, they have gone further and criticised the use of publicly available images (and especially of associated data), linking this to the fact that their selection may depend on companies. This is a potential source of problems, both due to the limitations placed on access to certain images. In addition, there is a risk of possible changes in access to these images (some of which may not, for example, be available in the future) (Pickering et al., 2020).

In the same vein, Donaire et al. (2014) warned of how the use of only publicly available images could influence the final result by excluding a substantial proportion of images associated with private events. This led these researchers to underline that their research did not include the preferences of all tourists but only those who had shared their photographs via social media. This is a warning that few authors seem to have heeded. Recent studies, such as those by Hauser et al. (2022), continue to rely on a selection of images from public profiles.

Other authors have placed more emphasis on highlighting the implications that using publicly available images may have for research. For example, Paül i Agustí (2020a, 2020b) and (Paül i Agustí and Dos Santos Costa, 2023) have pointed to potential sources of bias in the analysis of areas visited by tourists due to studies relying solely on publicly available images. Similarly, Li et al. (2023) have highlighted the need to evaluate the bias that may derive from research partially ignoring the way in which images are perceived by excluding the images captured by those who do not share their photographs on Instagram.

To the best of our knowledge, one of the few studies that has compared Instagram images from both public and private profiles was that by Arnold and Casellas Connors (2022). That study did not, however, focus on tourist images; instead, it analysed the experience of a group of 74 minors, aged 16–18, during their semester at college. The results obtained revealed important differences. The messages and publicly available images tended to be visually appealing and were all positive. They also used considerably longer captions and portrayed a greater range of activities and emotions than other students. This is something that reinforces differences between public and private profiles on Instagram and highlights the need for closer analysis to better understand the use that tourists make of public and private postings.

3. Methodology

3.1 Study area

The study focused on the Italian city of Turin (Torino, in Italian), which had 848,748 inhabitants, in 2021. This is a city that had traditionally been famed for its industry. However, since the end of the 20th century, the crises suffered by some of the city’s most important companies in this sector have forced a functional rethink, with one of the sectors that it was decided to promote being that of tourism. To increase the attractiveness of the city, it was decided to organise a series of major events, which included the Winter Olympic Games of 2006. The city also decided to renovate its important cultural heritage and particularly that related to the Savoy monarchy (Paül i Agustí, 2009). Because of subsequent investment, tourism in the city has surged in recent decades, rising from 760,000 arrivals in 2001 to 5,000,000 in 2022 (Regione Piemonte, 2023).

3.2 Sample

A group of 122 Spanish tourists, aged between 19 and 23, participated in the collection of data in situ; all of them were first-time visitors to the city. The choice of this age profile was motivated by the previous finding that the 18–24 age group is the one that most uses Instagram (30.8%) (Statista, 2023). As a result of several problems with applications and mobile phone batteries, and the lack of quality of some of the routes followed, the number of cases finally analysed was limited to 70.

3.3 Research design

The research design was sequential. Before the visit, and without the participants having received any information about their future visit, the participants were asked what they knew about the tourist attractions of Turin. The main objective was to identify if the participants had any previous image of the city that could lead to a bias (especially previous visits or relatives who lived there). A brief qualitative interview was conducted with the participants to ascertain whether they had been to or had any relationship with Turin. None of the participants indicated any connection with Turin. In addition, they were asked to make a list on paper of “the most relevant tourist elements of Turin”. Finally, the meeting was used as an opportunity to explain the functioning of the instruments employed to collect the data.

They subsequently made a visit to the city, on 21 and 22 October, 2022. On the evening of the 21st, the group arrived in Turin. The baseline itinerary for the study was conducted on the 22nd (Saturday) from 8:00 am to 9:00 pm. At the time, in order not to affect the results, they were not told the objectives of the study. All that was asked of the participants was that they should make a tourist visit to the city and have a tool activated in their mobile phones that would register their routes. Each tourist had their own accommodation, but in all cases, it was in the historic centre of the city (around the Royal Palace). The duration and direction of the itinerary were free and each participant determined it.

The tool used to record the itinerary was the Wikiloc application. This application was downloaded to the participant's mobile device beforehand. When starting the route, the user presses a button and the application automatically records the itinerary. Upon completing the route, the user presses “finish”. Based on this process, once they had completed their visits, the participants located the places they had photographed on a map of the city. This step allowed us to determine the total number of images taken by the participants (9,522). The participants were then asked whether or not they had shared each photograph and whether they had shared it privately via Instagram, or whether they had shared it publicly via Instagram. The quality of the sample was verified through a series of random checks (relating to approximately 3% of the images taken).

Regarding this aspect, it should be noted that when public and private images are mentioned, it is done with reference to the characteristics of the Instagram account. A public account is accessible to everyone, whereas a private account may only be accessible to the user or also to family, friends or followers. Instagram does not allow users to choose between private or public for a single post when sharing a photo. However, it should be noted that a single participant may have had different accounts where they shared images, some public and others private.

Once the map had been completed, the participants were asked to make a written reflection about why they had decided to either share or not share their different photographs. They were able to reply as they liked; there was no fixed duration, format or instructions.

3.4 Data analysis

The information regarding the most relevant tourist attractions in Turin was directly extracted from the list provided by the participants.

The information generated by users on Wikiloc was exported in GPX format (GPS exchange format). The cartographic analysis was conducted using a GIS tool (ArcGIS 10.8). The various layers were merged into a single layer.

Inverse distance weighting (IDW) has been used to spatially map and compare the obtained values. IDW is a spatial interpolation technique enable discrete measurements to be converted into a continuous spatial distribution. Like any interpolation function, IDW works with a set of sample points (L1, L2, […] Ln) and calculates the value for a new location L. IDW interpolation explicitly works on the assumption that things that are close to one another tend to be more similar than those that are further apart. This approach also allowed us to include examples of exceptional behaviour within the data set, such as places with a high impact factor located in areas with few sights with a GIS tool (ArcGis 10.8). The default values were used. The interpolations of areas without identified images were established on the basis of the 12 spatially closest values.

Finally, for the analysis of the texts written by the participants, a content analysis was applied. The information was coded and grouped according to the motivations of tourists for taking and sharing photographs. This process was performed manually.

4. Geolocalisation of the areas photographed and shared by the tourists

For the analysis of tourist mobility, the assumption was made that the tourist nodes represented the places visited (and photographed) and that the edges denoted movement flows (Mariani & Baggio, 2020). An initial analysis of the distribution of tourist movements showed that they had covered an area of 8.75 km² within the urban nucleus of the city (Figure 1). This was, however, a somewhat misleading statistic, as the majority of the tourists only moved within a much smaller area: the city’s historic centre. The historic centre included the greatest density of routes and all of the tourists analysed passed through it at one time or another. This distribution coincided with those previously observed by other authors (Donaire et al., 2014). Outside this central area, which houses the majority of the city’s historic royal residences, the visits were more specific. One of the tourists visited the city cemetery, whereas six others visited the Juventus Stadium, which is located more than 6 km from the city centre. It should be underlined that those who went to the stadium all used public transport, which explains the coincidence of their itineraries.

The first thing that was evident from the results obtained was the minimal coincidence between the elements that the tourists had said that they knew about when they completed the pre-visit survey and what they actually photographed (Table 1). The majority of the elements cited by the future tourists had been generic and were not identifiable on a map. Amongst the elements that could be located on the map, it is relevant to highlight that only the Juventus Stadium was photographed by the same number of tourists who had indicated previous knowledge of it. This points to a high degree of motivation previous to the visit to this particular destination, which was located outside the city centre. This level of motivation was not repeated with other areas, about which the participants had a low level of knowledge. These were, however, photographed by a greater number of people than those who had declared prior knowledge of them. The only exception was the Torino FC Stadium, which had been cited by one person but was not photographed by anyone.

The movements of the tourists within the city did not closely correspond with the points photographed. The majority of the photographs were taken between the River Po and the Piazza San Carlo square. Outside this area, no point photographed by more than 25% of participants was found (Figure 2). There was no place in the city that was photographed by all the tourists. However, the most photographed point coincided exactly with the place where most of the tourist routes coincided: the Piazza Castello square. This point was photographed by 65 tourists (92.9% of the total). The second and third points which were most photographed were located at the extremes of the historic city centre (the area which was most visited): the Piazza Vittorio Veneto square (photographed by 55 tourists; 78.7%) and the Carignano Palace (captured by 52 tourists; 74.3%). Once the tourists reached these points, they took photographs and then returned.

Outside this central area, the number of elements photographed was extremely limited. Quite near the historic centre of the city, a number of places were photographed, including the Porta Nuova railway station (20 tourists; 28.6%) and the market area of Porta Palazzo (12 tourists; 17.1%). However, as the distance from the centre grew, the number of photographs taken fell. Outside the city centre, the only place that the tourists photographed was the Juventus Stadium (15 tourists; 21.4%). The rest of the points photographed that were distant from the city centre corresponded to restaurant establishments, places where the tourists were staying or other places that they photographed from a means of transport taking them to the Juventus Stadium.

Just as there was a spatial difference in the distribution of the images, there was also a clearly observable difference in how the tourists shared their photographs on Instagram. The first thing to highlight is that the 70 tourists analysed took a total of 9,522 photographs. This means that they took an average of 136 photographs per person but with a significant degree of variation. This ranged from 734 images captured by the person who took most photographs to only 20 by the person who took fewest. The majority of the tourists took between 100 and 200 photographs (with a median of 146 photographs per tourist).

Something else to highlight is that the majority of the photographs taken were shared; only 1,817 photographs (19.1%) were not shared. However, in many cases, the photographs were only shared privately on Instagram (4,288; 45%). In other words, a substantial number of the photographs taken by tourists were not made public. In fact, only 3,417 photographs (35.9% of the total) were shared publicly via Instagram.

Another fact to highlight was the difference in behaviour at the moment of making images public. 50% of the tourists said that they had not shared any of their images publicly on Instagram. At the other extreme, one tourist said that they had shared 150 images via Instagram. In fact, 7.7% of the tourists (those who had publicly shared more than 50 photographs) were responsible for 36.4% of all the photographs that were shared publicly. This suggests that the distribution of public images via Instagram could largely be based on the behaviour of relatively few tourists.

There were also significant differences in the spatial distribution of the images according to whether they were shared privately or publicly (Figure 3). In absolute terms, the publicly shared photographs tended to represent the historic centre of Turin and to have been taken in the proximity of the most representative monuments of the city, and particularly near the Mole Antonelliana and Royal Palace, and also the Juventus Stadium. The photographs that were shared privately followed a similar distribution pattern. However, the images that were not shared on Instagram tended to mainly focus on Turin’s historic centre, with monuments, areas and shops being photographed various times and by different people. In fact, of the 116 places identified, 53 (45.7%) were not publicly shared on Instagram. Images of these places were therefore clearly underrepresented on the social network.

However, when the total number of pictures taken by tourists was compared to the pictures shared publicly on Instagram (Figure 4), several significant differences were observed. There were very few places in the city where the images that were made public via Instagram faithfully represented the whole set of photographs taken by the tourists. In fact, this only applied to some of the main streets in the city (the Via Po and part of the Quadrilatero Romano) and the area around the Juventus Stadium.

The historic centre of Turin was underrepresented on Instagram, with tourists photographing many more aspects of this area than they shared publicly. This implies that some such points could be overlooked if only images made public on Instagram were analysed. However, this situation was reversed in the case of the best-known monuments in the city: they had a greater presence in the images that were made public on Instagram than the weight that they should have had based on the whole set of photographs taken. A very large number of photographs, mainly corresponding to places such as the Palazzo Madama, Mole Antonelliana and the historic palace of the University of Turin, that were publicly shared on Instagram effectively over-represented these monuments.

The same type of over-representation in photographs that were made public was also observed for some places that were further from the city centre. Good examples of this were the market at Porta Palazzo, the Piazza Statuto square and the Campus Luigi Einaudi of the University of Turin. Unlike in the case of the best-known monuments, relatively few photographs were taken at these points, but the few that were tended to be shared publicly. The same phenomenon was observed in the area located near Turin’s historic centre, and especially to its northwest. These areas were not photographed very much, but the photographs were widely shared, resulting in an over-representation of these areas.

Finally, it is necessary to underline the fact that, outside the most central area of the city, there were a series of zones in which the presence of only privately shared images predominated. Many of these points corresponded to places providing tourist accommodation and/or restaurants. These are areas about which tourists do not tend to publicly share the images than they photograph.

5. Justifications made by the tourists for sharing their photographs publicly

As can be seen from the map presented above, there were clear spatial differences between the distribution of the images that were shared publicly and the whole set of the images taken. The responses that the tourists gave regarding their motives for sharing images of some places, but not of others, were “factors of social–psychological motivation (i.e. social interaction, ideal-self presentation, true-self presentation) and an important personal trait (public self-consciousness)” (Jun, 2022, p. 2).

When the tourists were questioned about the different places that they photographed, it was possible to observe certain nuances in their responses. Firstly, the density of people in a particular area was identified as an element that motivated people to take photographs: “of all the photographs that I have taken, some are the result of my own personal initiative […] while others were the result of a feeling of obligation, or due to social pressure, on seeing that many of my colleagues were taking the same photo […]; for example, the photos that I took at the Carignano Palace, say nothing to me” (woman, 66 photographs taken, 4 shared privately, none shared publicly). Some tourists went even further: “on many occasions, places that were really worth photographing were discarded for the simple reason that they were not widely recognised or not popular on the Internet” (man, 220 photographs taken, 22 shared privately and five shared publicly). This is a phenomenon that of taking photographs based on imitation, which has also been analysed in social psychology (Apaolaza et al., 2021).

As a result, many of the photographs taken were of areas that were either already recognised or where there were other tourists taking photographs. Even so, many of these photographs were not subsequently shared: “We may not particularly like what we are photographing and may perhaps even be indifferent to it, but as it is a symbol, it seems as if it should be considered essential to photograph, if only to prove that you have been there” (woman, 66 photographs, four shared privately, none shared publicly). The phenomenon described by the participant coincides with that shown in Figure 4, in which the central areas of Turin: the ones concentrating the greatest number of tourists, appeared to be clearly over-represented in the images that were made publicly available. For example, at the node level: “the photos of museums and palaces are not as attractive on the networks, so they are less published. Natural spaces are more attractive to followers” (woman, 500 photographs, six shared privately and four publicly). This is a situation that was also observed on the map, where the Royal Palace was underrepresented to a greater degree than its gardens.

However, looking beyond tourist resources, decisions about which images of places to share on social networks tended to be made based on what tourists had previously seen posted on these same networks: “the areas that are most popular are the ones that tend to be ultimately featured on social networks because by labelling places in this way you can obtain more likes and more visits” (woman, 212 photographs taken, 159 shared privately and 53 publicly). This is a phenomenon that can lead tourists to modify their planned routes to specifically take in these more popular places. Places that appear to have been clearly over-represented in the publicly available images, like the Porta Palazzo market, may not, therefore, be representative of the behaviour of tourists who are not on Instagram.

In the same vein, some tourists admitted that they were not interested in the veracity of their images: “if it was a beautiful image, but not one that was particularly true to reality, and I liked all of the elements that formed part of it, I made it public” (woman, 203 photographs taken, 15 shared privately and three publicly). As a result, the reality of the city was not necessarily that shown publicly. Instead, tourists often sought places, themes and specific framings that would give them images which they thought would be appropriate for Instagram: “The images that I wanted to finally publish on my social networks were always part of an attempt to offer the best photograph possible, taken from what seemed the right perspective and at the ideal moment” (woman, 143 photographs, 67 shared privately and three publicly).

This conditioning imposed by the network often went even further, often reaching the point at which tourists decided not to share certain photographs publicly. At this point, it should be remembered that 50% of tourists declared that they had not shared any of their images publicly. The main reason for this tended to be privacy: “The fact that the people who follow me on different networks know where I am, what I eat, where I sleep […] is something that I don’t feel completely comfortable about” (woman, 70 photographs, none shared either privately or publicly). Or: “I don’t want to share photos in which I appear’ (Woman, 131 photographs, none shared either privately or publicly). Similarly, there were some criticisms of the very act of posting images: ‘I wanted the photos to be souvenirs, rather than a way of showing off” (woman, 48 photographs, nine shared privately, none shared publicly).

Other tourists pointed to motives that were rather more personal: “A lot of the time, when we are really enjoying ourselves, we completely forget to take photos or videos, because we prefer to enjoy the experience and the moment” (woman, 66 photographs, four shared privately, none shared publicly). Finally, it should be added that one of the tourists stated that he had not been able to photograph one of the places that he visited because it was prohibited. This is another factor that is not taken into account in most analyses of public images.

These are examples of cases in which tourists took photographs, but without making all of them publicly available via Instagram. These are images that are not normally considered by the majority of most current research, which analyses images that are publicly available on Instagram. This is a limitation that could have altered the results of this study.

6. Theoretical implications

As noted by authors such as Li et al. (2023, p. 12), “the relationship between destination image congruence and tourist experience evaluations differs by attraction type and level”. The present work makes it possible to identify how these differences are spatially expressed.

Tourists who publicly share their photographs on Instagram tend to over-represent certain places. In the majority of cases, these are areas near to the most recognised places and ones that present certain characteristics that make them particularly original; certain attractive typologies, such as parks or green zones, which are often shared; and areas that have already enjoyed previous recognition on Instagram and which tourists feel an obligation to share. This implies that some types of places will tend to be underrepresented. The present research revealed two distinct typologies: the most emblematic monuments in the city, whose images were widely shared on Instagram but which were featured in a proportionally greater number of photographs and places where tourists carried out their private activities (particularly relating to their accommodation).

The differences that exist between the photographs that are shared publicly and privately imply that certain affirmations that suggest using Instagram as a source for knowing about tourist demand (Li et al., 2023) or counting numbers of visitors (Kim et al., 2022) should be re-evaluated. As Jun (2022) already warned, it is necessary to know to what extent publicly shared images are representative of all tourist experiences to guarantee calculations that adjust to reality.

The distribution of publicly shared images in our study also partially contradicted that presented by Hunter (2008), who claimed that the areas photographed by tourists are mainly associated with heritage and are those described in tourist information material. Such places continue to be photographed, but only “natural landscape spaces” tend to be publicly shared on Instagram. Furthermore, and as highlighted by Stylianou-Lambert (2012), the increase in the number of photographs taken thanks to the availability of digital media has not generally been accompanied by the incorporation of new sights; the majority of most cities remains unphotographed, and does not appear in either publicly and privately shared photographs.

The spatial distribution observed showed that the public images shared on Instagram were rarely redundant with respect to the whole set of images taken by tourists. This contrasted with what would have been expected, according to the literature, from a study based purely on publicly available images. On the other hand, it clearly showed how some points, despite enjoying great visibility on Instagram, were visited by relatively few tourists. These are considerations that could help us to better understand the distribution of tourism.

7. Practical implications

The proposed methodology can contribute to a better understanding of the extent to which Instagram images can help evaluate the platform's reliability as a source of tourism data. By revealing the gaps between the photos tourists share publicly and the full spectrum of pictures they capture, it underscores the need for a diversified destination marketing strategy that addresses both the public image and private preferences of tourists. This approach can help practitioners craft strategies that appeal to both the overt and subtle interests of tourists.

Being aware that Instagram public images only capture a portion of the places tourists visit may benefit the different stakeholders of the tourism industry. The results obtained have contributed to unveiling inequalities in the spatial distribution of tourism, which could help tourism marketers to produce and implement better marketing campaigns. For example, tourism packages can be created that differ from those promoted by competitors and that better fit the tourist’s expectations. This would create new experiences, making them more immersive and creative, in line with international trends in tourist motivations. Improving the understanding of tourist behaviour can help implement strategies that foster cooperation and prevent mismanagement of expectations from causing conflict or frustration among tourists.

At the same time, the results may play a crucial role in examining, evaluating and revising tourism policies and planning strategies. Tourism management might tend to rely solely on images posted on social media. However, posted images only capture a part of tourists' activities. There are aspects of their behaviour that remain unseen but can also have positive and negative impacts on the city. Keeping this in mind can help better manage tourist flows, avoid overcrowding in certain areas or highlight places with tourism potential even if they are underrepresented in public images on social media. To achieve this, planning authorities will need to develop strategies that encourage tourists to share images beyond the usual ones. This process may require new marketing tools.

If this change is achieved, local communities can also benefit from a more varied image of the city. This process can help strengthen local identity and self-esteem of residents thanks to tourist recognition.

8. Conclusions

The spatial distribution of the images shared publicly on Instagram only partially coincides with the whole set of images taken by tourists. In this regards, the study validates the intuition pointed out by authors such as Donaire et al. (2014), indicating that the use of only publicly available images could influence the outcome by excluding a significant proportion of images associated with private events. Academic studies based on publicly shared images on Instagram should alert to this limitation.

This does not, however, mean that research based on Instagram images should be ignored. Publicly shared images can give a good initial approximation of the touristic reality of a particular territory. Furthermore, it is important to be aware of the fact that some tourists prepare their visits based almost entirely on what they have seen on Instagram. That said, one must not confuse studies based on images shared publicly on Instagram with studies that analyse the behaviour of all tourists, or that of all the users of Instagram.

The present study shows the need to look beyond publicly shared images if we want to obtain a faithful representation of the behaviour of tourists as a whole. Only in this way will it be possible to obtain a good understanding of the image projected to potential visitors. Understanding this will permit improvements in areas such as marketing (Marine-Roig & Ferrer-Rosell, 2018) and urban management policies (Oguztimur & Akturan, 2016).

The findings of the current study have a number of practical implications. First of all, it is necessary to be aware of the fact that the reality that influences tourists extends beyond the images that they publicly share on Instagram. It is therefore important to avoid basing marketing and management policies on just the places featured in publicly shared images. If not, there is a risk of taking decisions based on the behaviour of some, rather than all, tourists. However, it is also necessary to be aware of the weight that Instagram posts have, particularly as a section of the population only seems to consult this source. This may lead to situations in which tourists discover that the reality at the destination is very different from what they had imagined after consulting Instagram (Moussalli, 2019). It is therefore necessary to find a balance between, on the one hand, the potential that Instagram offers for shaping the public image of a city and, on the other, the image that is promoted by tourists as a whole.

It is important to be aware of the fact that the present research had certain limitations that should be considered when interpreting its findings. The study sample had an over-representation of females and focused on a group of people aged between 19 and 23 years old. In this regards, the results should be considered valid solely for this age group. Different nationalities and age groups may have different preferences and exhibit different behaviour. For example, Wilson et al. (2012) reported that British and Swiss visitors were more likely to share travel photos than those from Spain. Interpreting and generalising the results of this study and applying them to other samples should therefore be performed with caution. It would also be interesting to analyse the role of influencers, as their views may have greater repercussions than those of other references. Likewise, another limitation is the fact that the study focuses solely on one city. Expanding sampling points and conducting replicated studies would help improve the understanding of the analysed phenomenon.

This article also opens the way for future lines of research. Firstly, it is important to know that there are places where it is prohibited to take tourist photographs. Secondly, there are people who decide not to take photographs. These are two types of behaviour that are difficult to identify via Instagram, but which may have an important influence upon how tourists decide to manage their time. These are questions that are often not taken into consideration. Similarly, an analysis of the content of the images would provide a better knowledge of tourist behaviour and help to ranking its positive and negative spatial consequences. Finally, it will be necessary to analyse the limitations and implications that relying solely on publicly available images may have for the tourism industry.

Figures

Figure 1

Routes followed by the tourists and the points photographed

Figure 2

The number of people who photographed each attraction

Figure 3

Distribution of the photographs according to whether they were shared publicly or privately or no tshared at all

Figure 4

The distribution of the photographs based on their public or private sharing status (Inverse Distance Weighted)

Table 1

Relevant elements in Turin that were cited before the visit (number of citations) and subsequently photographed

Generic elements		Specific elements		No. of tourists who photographed them
Nothing specific	46	Juventus Stadium	15	15
Gastronomy	23	City Hall	3	3
Architecture	9	Cathedral	3	38
Pasta	9	Mole Antonelliana	3	49
Football	6	Royal Palace	3	45
Mountains	6	Roman remains	1	21
Pizza	6	Torino FC Stadium	1	0
Climate	2
FIAT	2
Language	1
Museums	1

Notes:

n = 70; Multiple replies were possible

Source: Author’s own research