Sustainability analysis on Urban Mobility based on Social Media content

Urban transport became an important element in the promotion of strategies towards sustainability, in fact one of the challenges posed by booming urban populations is the question of mobility. Traditional travel survey methods used to study urban mobility are very expensive, and the data collected are of poor quality. This is mainly explained because of the difficulty of getting a representative sample of the population, and the lack of motivated participants. Therefore, travel surveys are carried out less and less frequently, and the result is that good travel data is not available to develop mobility and travel behaviour studies. Information and Communication Technologies (ICT) offer the opportunity to improve traditional travel survey methods, decreasing bias in the data, reducing respondent burden, and increasing data quality. On the other hand, nowadays the User Generated Content (UGC) is growing very fast in Internet. Social media have become a valuable source for knowledge but there is a big gap in the automatic Sentiment Analysis with Semantic taxonomy annotation of online textual content. The aim of this research is to identify sustainability issues related to urban mobility based in the perceptions and experiences that underlie in the UGC. The methodology follows a quantitative and qualitative content analysis using Sentiment Analysis techniques. This paper demonstrates empirically the feasibility of the automatic identification of the Sustainable Urban Mobility problems in the discourses generated by the UGC, through a powerful ad-hoc software combining Natural Language Processing and Sentiment Analysis field tools. The main contribution of this work is the development of a tool and methodology on sustainability analysis on urban environment. Our approach enriches the data of the traditional surveys, extends traditional analysis with Big-Data methods, using data mining algorithms and Natural Language Processing techniques to extract urban mobility information from Social Media data. These data include important information about activities and travels, and can help to improve our understanding of urban mobility

Tourism and ICTs: Advances in Data Science, Artificial Intelligence and Sustainability: Proceedings of the TURITEC 2023 Conference, October 19–20, 2023, Málaga, Spain

Subido al repositorio por el editor (Real Decreto Legislativo 1/1996, art. 8)This open-access book presents the best research papers from the XIV International Congress on Tourism and Information and Communications Technologies (TURITEC2023), held in Málaga, Spain from 19 to 20 October 2023. The book explores the profound impact of COVID-19 on the tourism industry and the increasing importance of digitalization and Information and Communication Technologies (ICTs) as key drivers for the industry's recovery, alongside sustainability. This curated collection of research papers offers conceptualizations, methodologies, analyses, and empirical case studies that illuminate the path to a resilient and sustainable future for tourism.Instituto Andaluz de Investigación e Innovación en Turismo. Unviersidad de Málag

Diversity of journalisms. Proceedings of the ECREA Journalism Studies Section and 26th International Conference of Communication (CICOM) at University of Navarra

These Proceedings gather the research works presented to the Conference “Diversity of Journalisms: Shaping Complex Media Landscapes”, held in Pamplona (Spain), the 4th and 5th of July, 2011. This event was co-organised by ECREA Journalism Studies Section and the School of Communication of the University of Navarra

Two-stage model of destination image : exploring the consequences

In the globalized world tourism industry is acknowledges as an opportunity to enhance a country’s overall development. As research suggests, a destination’s main tool to become attractive is the destination image – the main pull factor in tourists’ decision-making process. Hence, there has been extensive research on destination image to examine its formation and relationships with other tourist decision-related constructs. Although acknowledged as a dynamic process for its feature of developing over time in several stages, there has been no attempt to examine pre- and post-visit destination images in integration. Therefore, based on the call by several scholars and theoretical support of its importance, the study set its purpose to examine the direct and indirect impact of pre-visit destination image on post-visit image and destination image evaluation outcome variables. For this purpose, a structural equation modelling of the relationships among pre- and post-visit images, perceived value, overall satisfaction, and word-of-mouth intentions was established. The data was collected from international tourists in Uzbekistan at two different points in time to test the hypotheses outlined in the model. In total, 178 paired questionnaires were collected. It was analysed on SmartPLS3. The findings confirmed the statistically significant direct impact of pre-visit image on post-visit image, and indirect impact of the pre-visit image through the post-visit image on the variables closely linked to the evaluation of the destination like satisfaction, value, and word of mouth intentions, hereby referred as destination image evaluation outcomes

Radio evolution: conference proceedings

Fundação para a Ciência e a Tecnologia (FCT