Creating value from Social Big Data: Implications for Smart Tourism Destinations

Vecchio, Pasquale Del; Mele, Gioconda; Ndou, Valentina; Secundo, Giustina

doi:10.1016/j.ipm.2017.10.006

Cited by 305 publications

(243 citation statements)

References 51 publications

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“…Applications are useful for tourists, but they are also of great importance for destinations. In fact, Big Data resulting from user-generated content and real-time analysis and synchronization of this data have become the main drivers of the value-creation process for an intelligent destination [44,46]. On the one hand, they make it possible for tourism profiles to be defined in more detail, both their sociodemographic profiles and their preferences, feelings and attitudes.…”

Section: Sustainable Smart Tourism Destinationsmentioning

confidence: 99%

Sustainable, Smart and Muslim-Friendly Tourist Destinations

2020

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Information and Communication Technology (ICT) tools are perfect for developing tourism. Several countries are making an effort to become smart and sustainable tourist destinations, making it easier for tourists to interact with their environment while at the same time improving the quality of life for local people. There are many studies of this process and the benefits it brings, although most of them approach the subject from a western traveler's point of view. This article aims to study the benefits of being a smart and Muslim-friendly tourist destination. An exploratory study was therefore carried out, including a bibliographical review of over one hundred secondary sources. We analyze the Muslim-friendly online services provided by nine destinations, and one of our principal conclusions is that these online services are of the greatest importance for a destination to be truly Muslim-friendly. We also conclude that such services allow companies to design tailored proposals and promote them through digital channels aimed at Muslim people.

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Section: Sustainable Smart Tourism Destinationsmentioning

confidence: 99%

Sustainable, Smart and Muslim-Friendly Tourist Destinations

2020

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“…We investigate these questions using data from a major publisher of YouTube content. With the increased availability of online user and customer data, there is the opportunity to use data‐driven personas derived directly from a system's users or a company's customer analytics data (Vecchio, Mele, Ndou, & Secundo, ), with each persona representing a distinct audience segment. Personas developed from this approach can be created automatically (Jung et al, ), which we did for this research.…”

Section: Methodsmentioning

confidence: 99%

Capturing the change in topical interests of personas over time

Jansen

Jung

Salminen

2019

Proceedings of the Association for Information Science and Tech

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In this research, we collect monthly content consumption and demographic data from YouTube over two years for a large media publisher. We use automation to generate 15 personas each month and examine the consistency of the generated personas over time. We find that there are 35 unique personas in total for the entire period, reflecting the changes in the underlying audience population. For each persona, we generate topics of interest and identify the top three monthly topics for each of the 35 personas following an identical algorithmic approach each month. We then compare the sets of topical interests of the personas month‐over‐month for the entire two‐year period. Findings show that there is an average 20.2% change in topical interests and that 68% of the personas experience more topical change than topical consistency. Findings suggest that the topical interests of online audiences are fluid and changes in the underlying audience data can occur within a relatively short period, resulting in the need for constant updating of personas using data‐driven methods. The implications for organizations seeking to understand their online audience are that they should employ routine data analysis to detect changes in the audience interests and investigate ways to automate their persona generation processes.

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“…Paid and free data from online social media sources and remote sensing cater near-real-time data. Such data have been increasingly used for a huge range of applications including human settlement mapping [9,10], land use and land cover mapping [11], understanding socio-economic conditions [12], tourism studies [13][14][15], etc. In recent years, many studies have proposed various ways to discover tourism destinations and activities.…”

Section: Introductionmentioning

confidence: 99%

Using Volunteered Geographic Information and Nighttime Light Remote Sensing Data to Identify Tourism Areas of Interest

et al. 2019

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Easy, economical, and near-real-time identification of tourism areas of interest is useful for tourism planning and management. Numerous studies have been accomplished to analyze and evaluate the tourism conditions of a place using free and near-real-time data sources such as social media. This study demonstrates the potential of volunteered geographic information, mainly Twitter and OpenStreetMap, for discovering tourism areas of interest. Active tweet clusters generated using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm and building footprint information are used to identify touristic places that ensure the availability of basic essential facilities for travelers. Furthermore, an investigation is made to examine the usefulness of nighttime light remotely sensed data to recognize such tourism areas. The study successfully discovered important tourism areas in urban and remote regions in Nepal which have relatively low social media penetration. The effectiveness of the proposed framework is examined using the F1 measure. The accuracy assessment showed F1 score of 0.72 and 0.74 in the selected regions. Hence, the outcomes of this study can provide a valuable reference for various stakeholders such as tourism planners, urban planners, and so on.

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Creating value from Social Big Data: Implications for Smart Tourism Destinations

Cited by 305 publications

References 51 publications

Sustainable, Smart and Muslim-Friendly Tourist Destinations

Sustainable, Smart and Muslim-Friendly Tourist Destinations

Capturing the change in topical interests of personas over time

Using Volunteered Geographic Information and Nighttime Light Remote Sensing Data to Identify Tourism Areas of Interest

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