Geo-Crowdsourcing Contributions for Cultural Mapping

Over the years, cultural mapping methods have been used in several applications and contexts, for diverse cultural assets and to create new conditions for the development of local and regional resources. These methods were inspired by the development of big urban centres and regions, which have been the great engine of cultural mapping growth. The main objectives of the present paper are to provide a literature review on cultural mapping methodologies and to develop exploratory research on crowdsource tools on creative tourism which were applied to one Portuguese municipality in 2017. The research was supported by the implementation and integration of geographic information systems (GIS) and web mapping, which will become part of the solution for the growth of less developed territories and to make more interactive tourist activities. Web mapping’s contribution to enhance crowd participation was measured via analysis of 12 digital photos shared through crowdsourcing. The originality of this research lies in the attempt to develop a new model for creative tourism, trying to extend the implementation of Web Mapping crowdsourcing to deprived low density territories. Results show how public participation can be amplified for the tourism market by crowdsourcing tools. These tools look very promising since they can help several members of the public at different ages to contribute to territorial knowledge, engage in activities, and collaborate through digital tools. It is a step to fulfil the lack of studies in this subject and it contributes to the way we think about future studies

Sensing the Cultural Significance with AI for Social Inclusion

Social Inclusion has been growing as a goal in heritage management. Whereas the 2011 UNESCO Recommendation on the Historic Urban Landscape (HUL) called for tools of knowledge documentation, social media already functions as a platform for online communities to actively involve themselves in heritage-related discussions. Such discussions happen both in “baseline scenarios” when people calmly share their experiences about the cities they live in or travel to, and in “activated scenarios” when radical events trigger their emotions. To organize, process, and analyse the massive unstructured multi-modal (mainly images and texts) user-generated data from social media efficiently and systematically, Artificial Intelligence (AI) is shown to be indispensable. This thesis explores the use of AI in a methodological framework to include the contribution of a larger and more diverse group of participants with user-generated data. It is an interdisciplinary study integrating methods and knowledge from heritage studies, computer science, social sciences, network science, and spatial analysis. AI models were applied, nurtured, and tested, helping to analyse the massive information content to derive the knowledge of cultural significance perceived by online communities. The framework was tested in case study cities including Venice, Paris, Suzhou, Amsterdam, and Rome for the baseline and/or activated scenarios. The AI-based methodological framework proposed in this thesis is shown to be able to collect information in cities and map the knowledge of the communities about cultural significance, fulfilling the expectation and requirement of HUL, useful and informative for future socially inclusive heritage management processes

Screening the stones of Venice: Mapping social perceptions of cultural significance through graph-based semi-supervised classification

Mapping cultural significance of heritage properties in urban environment from the perspective of the public has become an increasingly relevant process, as highlighted by the 2011 UNESCO Recommendation on the Historic Urban Landscape (HUL). With the ubiquitous use of social media and the prosperous developments in machine and deep learning, it has become feasible to collect and process massive amounts of information produced by online communities about their perceptions of heritage as social constructs. Moreover, such information is usually inter-connected and embedded within specific socioeconomic and spatiotemporal contexts. This paper presents a methodological workflow for using semi-supervised learning with graph neural networks (GNN) to classify, summarize, and map cultural significance categories based on user-generated content on social media. Several GNN models were trained as an ensemble to incorporate the multi-modal (visual and textual) features and the contextual (temporal, spatial, and social) connections of social media data in an attributed multi-graph structure. The classification results with different models were aligned and evaluated with the prediction confidence and agreement. Furthermore, message diffusion methods on graphs were proposed to aggregate the post labels onto their adjacent spatial nodes, which helps to map the cultural significance categories in their geographical contexts. The workflow is tested on data gathered from Venice as a case study, demonstrating the generation of social perception maps for this UNESCO World Heritage property. This research framework could also be applied in other cities worldwide, contributing to more socially inclusive heritage management processes. Furthermore, the proposed methodology holds the potential of diffusing any human-generated location-based information onto spatial networks and temporal timelines, which could be beneficial for measuring the safety, vitality, and/or popularity of urban spaces

Las redes sociales como instrumento de gestión de destinos turísticos

The main objective of this research focuses on determining the functions and application of social networks in the management of tourist destinations, with the aim of revealing the state of the art and degree of applicability. First, in order to fulfill the objectives and theoretical hypotheses, a bibliographic analysis is carried out, which leads to the elaboration of the state of the art regarding the topic on which this doctoral thesis revolves. In this sense, the state of the art of the research is elaborated from a systematic analysis of the scientific literature on smart destinations (concept, dimensions, components, management systems) and their integration with social networks. In order to respond to the second group of specific objectives and hypotheses, the methodology applied was quantitative, based on the analysis of a series of data from Spanish tourist destinations in terms of their presence and management of social networks. The quantification of these variables, for each of the 78 tourist destinations (among which were all the smart tourist destinations, hosted by the SEGITTUR project), allowed us to apply different quantitative statistical techniques, such as: a) Pearson's correlation analysis, to establish the type of interrelation between the independent variable (number of visitors) and the dependent variables, which referred to the presence and management of the destinations on the web and in social networks; and b) to determine the degree of use of social networks by the smart destinations with respect to the others, an ANOVA analysis was carried out between the variables of the most visited destinations with respect to those of the smart destinations, in order to detect possible statistically significant differences between the two groups of destinations with respect to their management of social networks. Finally, in order to fulfill the third group of objectives and specific hypotheses, and to demonstrate whether there is complementarity between the data provided by social networks and those offered by official statistics, in terms of tourism demand, a qualitative methodology is followed, since it is based on an exploratory case analysis. In this sense, the change experienced by the behaviors and feelings of tourists visiting Andalusia as a result of COVID-19 is analyzed, both with data from the Andalusia Tourism Situation Survey (ECTA, 2020) and by means of a sentiment analysis using Twitter data. For the exploratory sentiment analysis, using Twitter, the statistical program R and the library package (rtweet) were used to retrieve messages from the social network Twitter (tweets). Machine learning sentiment analysis algorithms were then applied to the resulting data. Therefore, based on the results obtained from this doctoral thesis, we believe that it is necessary for tourist destinations to have a professional specialized in the management of social networks (social media manager), as this will allow the destination to make the most of its presence in social networks. In short, it is considered that research focused on the applicability of social networks to the management processes of tourist destinations is still in its early stages of development, especially if we analyze the real applicability it is having in specific tourist destinations. This recommendation is important both when it comes to adapting to the progressive development of new technologies, as well as to the evolution of the behavior and profile of tourists, who are increasingly familiar with the use of new technologies, and demand flexible experiences adapted to their preferences, among other characteristics.El objetivo principal de esta investigación se centra en determinar las funciones y aplicación de las redes sociales en la gestión de los destinos turísticos, con objeto de poner de manifiesto el estado de la cuestión y grado de aplicabilidad. Primero para dar cumplimiento a los objetivos e hipótesis teóricas, se realiza un análisis bibliográfico, el cual da lugar a la elaboración del estado del arte respecto al tema sobre el que gira la presente tesis doctoral. En este sentido, el estado del arte de la investigación se elabora a partir de un análisis sistemático de la literatura científica acerca de los destinos turísticos inteligentes (concepto, dimensiones, componentes, sistemas de gestión) y su integración con las redes sociales. Para dar respuesta al segundo grupo de objetivos e hipótesis específicas, la metodología aplicada fue de tipo cuantitativa, basada en el análisis de una serie de datos que arrojan los destinos turísticos españoles en cuanto a su presencia y gestión de las redes sociales. La cuantificación de estas variables, para cada uno de los 78 destinos turísticos (entre los que se encontraban todos los destinos turísticos inteligentes, acogidos al proyecto de SEGITTUR), nos permitió aplicar diferentes técnicas estadísticas cuantitativas, tales como: a) el análisis de correlación de Pearson, para establecer el tipo de interrelación entre la variable independiente (número de visitantes) y las variables dependientes, que se referían a la presencia y gestión de los destinos la web y en las redes sociales; y b) para determinar el grado de utilización de las redes sociales por parte de los destinos turísticos inteligentes respecto a los restantes, se realizó un análisis ANOVA entre las variables de los destinos más visitados respecto a las de los destinos turísticos inteligentes, con objeto de detectar posibles diferencias estadísticamente significativas entre ambos grupos de destinos en lo que respecta a la gestión que hacen de las redes sociales. Por último, para dar cumplimiento al tercer grupo de objetivos e hipótesis específicas, y demostrar si existe complementariedad entre los datos que arrojan las redes sociales y los que ofrecen las estadísticas oficiales, en lo que respecta a la demanda turística, se sigue una metodología de corte cualitativa, ya que se fundamenta en un análisis de caso, de carácter exploratorio. En este sentido, se analiza el cambio experimentado por los comportamientos y sentimientos de los turistas que visitan Andalucía como consecuencia de la COVID-19, tanto con los datos de la Encuesta de Coyuntura Turística de Andalucía (ECTA, 2020) como mediante un análisis de sentimientos con datos de Twitter. Para el análisis exploratorio de sentimientos, mediante Twitter, se utilizó el programa estadístico R y el paquete de biblioteca (rtweet) para la recuperación de mensajes de la red social Twitter (tweets). A continuación, se aplicaron algoritmos de análisis de sentimientos mediante aprendizaje automático a los datos resultantes. Por todo ello, a partir de los resultados que se obtienen de esta tesis doctoral, consideramos que se hace necesario que los destinos turísticos cuenten con un profesional, especializado en la gestión de redes sociales (social media manager), pues ello permitirá al destino sacar el máximo provecho a su presencia en las redes sociales. No en vano, esta actuación posibilitará el máximo desempeño de las múltiples funciones que, a lo largo de la investigación, se han puesto de manifiesto, que pueden desempeñar esta herramienta, dentro de los procesos de gestión de los destinos turísticos En definitiva, se considera que la investigación centrada en la aplicabilidad de las redes sociales a los procesos de gestión de los destinos turísticos está aún en sus primeras etapas de desarrollo, sobre todo si analizamos la aplicabilidad real que está teniendo en destinos turísticos concretos. Esta recomendación es importante tanto a la hora de adaptarse al progresivo desarrollo de las nuevas tecnologías, como por la evolución que viene experimentando el comportamiento y perfil de los turistas, los cuales, cada vez, están más familiarizados con el uso de nuevas tecnologías, y demandan experiencias flexibles y adaptadas a sus preferencias, entre otras características

Crowdsourcing the Reputation of Martin Luther King: Twitter as a Place of Memory

This dissertation develops the idea of crowdsourced memory. The term captures three important developments in the conceptualization, technological delivery, and analytical study of public memory. In terms of conceptualization, a crowdsourcing approach recognizes that the remembering of the past is an inherently collective and often competitive enterprise in which the public participates in the co-construction of memory and the meanings of memorial landscapes and places. A crowdsourcing approach also recognizes the growing influence of the Internet and social media as not just a means of communication, but also a system of cultural and place representation, as well as, a memory technology—a way of expressing views about the past, but also a way of recording the history of place experiences at places devoted to the past. The posting of experiences and opinions through platforms, such as, Twitter have dramatically expanded public expression and contribution to the project of remembering, interpreting, and re-interpreting the past. Finally, a crowdsourcing approach represents a new methodology that recognizes social media posts provide an important source of not only quantitative, but also meaningful qualitative data for scholars to understand how the legacy and reputation of individuals and organizations are communicated, consumed, and co-constructed by the public. This dissertation also employs qualitative geographic information sciences to examine the locational variation of the themes associated with each Tweet. This dissertation applies a crowdsource approach based on critical race theory to understand the reputational politics that surround the annual holiday dedicated to Dr. Martin Luther King Jr

NEGOTIATING THE SACRED: UNDERSTANDING IMPACTS TO IKS AND ITEK FROM USE OF REMOTE SENSING AND GIS TECHNOLOGIES WITHIN TRIBAL LANDSCAPES

How we see the world and ourselves in relation to it is largely achieved by the lens we are looking through and associated experiences within this relationship. This is additionally true when considering the acknowledged fact that Indigenous Knowledges are derived from natural and cultural sources and these assist in constituting the cultural identities of those Peoples associated with these sources. Presently there is a hunger for access and use of Indigenous Knowledges (IK) as never before seen in public ways, through a national Call for collaborative means to apply these knowledges to such as the issues we globally face as a result of Climate Change. What are Indigenous Knowledges? How are they created? Who holds these and can utilize them in public ways? These questions are an embedded aspect of this Call that requires attention. Further, what impacts exist that benefit, but also challenge, the endeavor to utilize Indigenous Knowledges outside local areas where they are derived? What of these sacred ways of knowing are being negotiated to attain their use? Five areas of concern were identified in response to these questions through application of An Indigenous Research Way (AIRW), a novel continuous improvement model for implementing Indigenous Research Methodologies and Methods, within research design and practice. Synthesizing these concerns into three themes, Education, Technology, and Tribal Leader Decision-Making, awareness was revealed of these as first level and gateway impacts. Indigenous ways of knowing, being, and doing operationalizes Indigenous worldviews about relationality and this as central to how Indigenous Knowledges Systems (IKS) are created and in turn create Indigenous Traditional Ecological Knowledges (ITEK). Understanding how we “see” ourselves in relation to this process is imperative. A burgeoning method for seeing landscapes, and they as sources of IK, is through use of remote sensing and Geographical Information Systems (GIS). This Phase I study, through a Kin-based Case Study and mixed-methods approach, sought to understand impacts to IKS and ITEK from use of these technologies within tribal landscapes through review and assessment of 73 ESRI tribal GIS public StoryMap projects, led by tribal practitioners, accomplished in 2017 - 2021. Assessment provides there exists an assumption that identifying as being Indigenous includes being a holder of cultural knowledges and that these are utilized at will and regularly. The data troubles this assumption with respect to tribal individuals trained as practitioners of these technologies and their use of ITEK then provided through public digital media. Impacts to IKS and ITEK reveal enhancements and also replacement of the “seeing” accomplished by Indigenous People through technological means and the public perceptions of their cultural lifeways and persona of being Holders of Indigenous Knowledges. These impacts are broad in their implications as they attend to not only understandings of past and present access to ITEK but also future applications that brings the conversation into the realms of understanding being Indigenous off-earth