A Systematic Literature Review on Social Media Analytics and Smart Tourism

Viñan-Ludeña, Marlon-Santiago

doi:10.1007/978-3-030-03910-3_25

Cited by 9 publications

(5 citation statements)

References 54 publications

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“…gave rise to the link between their analysis and that of big data [34][35][36]. Therefore, much research has been devoted to social media analytics in general [37][38][39] and tourism analytics in particular [40][41][42].…”

Section: Introductionmentioning

confidence: 99%

Destination Image Analytics Through Traveller-Generated Content

Mariné-Roig

2019

Sustainability

109

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The explosion of content generated by users, in parallel with the spectacular growth of social media and the proliferation of mobile devices, is causing a paradigm shift in research. Surveys or interviews are no longer necessary to obtain users’ opinions, because researchers can get this information freely on social media. In the field of tourism, online travel reviews (OTRs) hosted on travel-related websites stand out. The objective of this article is to demonstrate the usefulness of OTRs to analyse the image of a tourist destination. For this, a theoretical and methodological framework is defined, as well as metrics that allow for measuring different aspects (designative, appraisive and prescriptive) of the tourist image. The model is applied to the region of Attica (Greece) through a random sample of 300,000 TripAdvisor OTRs about attractions, activities, restaurants and hotels written in English between 2013 and 2018. The results show trends, preferences, assessments, and opinions from the demand side, which can be useful for destination managers in optimising the distribution of available resources and promoting sustainability.

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Section: Introductionmentioning

confidence: 99%

Destination Image Analytics Through Traveller-Generated Content

Mariné-Roig

2019

Sustainability

109

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“…In the past, academics and researchers were particularly interested in the amount of data created each day by social media (Facebook, Twitter, Instagram, Sina-Weibo, blogs, news, etc.). The essential pillars of social media analytics are data from social media, users or people, industry, and technology [8]. To quantify tourist engagement on DMO social media, [9] provides a new social media index; they concluded that social media indices may be utilized to evaluate and monitor the effectiveness of DMO social media in tourism engagement.…”

Section: Tourism Management Systemmentioning

confidence: 99%

Comprehensive Survey for Designing and Implementing Web-based Tourist Resorts and Places Management Systems

Yazdeen¹,

Zeebaree²

2022

ACAD J NAWROZ UNIV

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Recently, development an efficient Tourism Management System (TMS), become an important issue in tourism toward industry. Internet act one of most common role in popularity information and data to the tourists by uploaded this information include the tourism places, distance through the World Wide Web. Tourism Management System can be understanding as a complete tourist fully integrated tourism web site. Such website or web application covers all the areas required, in order to display and view wide range of information for one place, to rapid serve connection between manager of place with tourism. It is the process of defining the purpose, vision, and goals of an organization, formulating policies and plans, and then allocating resources to execute the policies and plans, projects, and programs developed to meet those objectives. The major goal of these projects is for better giving a confederacy in managing, logging and logout, complaints and reports. Through the cultural consumption of visitors, tourism types have played a significant influence in the development of regional and local economies. An intangible purpose to build and promote cities and nations through promotion is addressed by a creative tourist system from a new paradigm. Economic, social, political, and cultural factors have all increased their regard for originality and inventiveness as a result of this development. The study attempts to clarifies and displayed various types of systems used by various tourism authorities had a positive possible effect on their operations by making tasks easier for their employees. Furthermore, the study discusses the main differences of these studies by comparing between some of these studies in order to gain the base benefices when new researcher want to make new TMS.

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“…enables researchers to identify patterns for tourism management and planning. While some researchers use the term online-travel reviews (OTRs) or UGC, all of the tourist content generated on social media can broadly be described as TGC, and this encompasses all social media platforms and networks (social networking sites, blogs/microblogs, content communities, forums–discussion) (Viñan-Ludeña, 2019).…”

Section: Related Workmentioning

confidence: 99%

“…Usergenerated content enables travelers to provide their opinions about hotels, restaurants or places they have visited, and users planning to visit such places can then use UGC to read recommendations and feedback beforehand. Since users are influenced by other people's opinions (Ampountolas et al, 2019;Viñán-Ludeña et al, 2020) it is important to be able to analyze all of this information in order to understand how travelers use and interact with the different social networks (Viñan-Ludeña, 2019). This work shows the perceptions of Twitter users of a tourist destination taking into account the season of the year and the language of each user, this information is useful in the pre-trip phase.…”

Section: Introductionmentioning

confidence: 99%

Analyzing tourist data on Twitter: a case study in the province of Granada at Spain

Viñán-Ludeña

Campos

2021

JHTI

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PurposeThe main aim of this paper is to build an approach to analyze the tourist content posted on social media. The approach incorporates information extraction, cleaning, data processing, descriptive and content analysis and can be used on different social media platforms such as Instagram, Facebook, etc. This work proposes an approach to social media analytics in traveler-generated content (TGC), and the authors use Twitter to apply this study and examine data about the city and the province of Granada.Design/methodology/approachIn order to identify what people are talking and posting on social media about places, events, restaurants, hotels, etc. the authors propose the following approach for data collection, cleaning and data analysis. The authors first identify the main keywords for the place of study. A descriptive analysis is subsequently performed, and this includes post metrics with geo-tagged analysis and user metrics, retweets and likes, comments, videos, photos and followers. The text is then cleaned. Finally, content analysis is conducted, and this includes word frequency calculation, sentiment and emotion detection and word clouds. Topic modeling was also performed with latent Dirichlet association (LDA).FindingsThe authors used the framework to collect 262,859 tweets about Granada. The most important hashtags are #Alhambra and #SierraNevada, and the most prolific user is @AlhambraCultura. The approach uses a seasonal context, and the posted tweets are divided into two periods (spring–summer and autumn–winter). Word frequency was calculated and again Granada, Alhambra are the most frequent words in both periods in English and Spanish. The topic models show the subjects that are mentioned in both languages, and although there are certain small differences in terms of language and season, the Alhambra, Sierra Nevada and gastronomy stand out as the most important topics.Research limitations/implicationsExtremely difficult to identify sarcasm, posts may be ambiguous, users may use both Spanish and English words in their tweets and tweets may contain spelling mistakes, colloquialisms or even abbreviations. Multilingualism represents also an important limitation since it is not clear how tweets written in different languages should be processed. The size of the data set is also an important factor since the greater the amount of data, the better the results. One of the largest limitations is the small number of geo-tagged tweets as geo-tagging would provide information about the place where the tweet was posted and opinions of it.Originality/valueThis study proposes an interesting way to analyze social media data, bridging tourism and social media literature in the data analysis context and contributes to discover patterns and features of the tourism destination through social media. The approach used provides the prospective traveler with an overview of the most popular places and the major posters for a particular tourist destination. From a business perspective, it informs managers of the most influential users, and the information obtained can be extremely useful for managing their tourism products in that region.

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A Systematic Literature Review on Social Media Analytics and Smart Tourism

Cited by 9 publications

References 54 publications

Destination Image Analytics Through Traveller-Generated Content

Destination Image Analytics Through Traveller-Generated Content

Comprehensive Survey for Designing and Implementing Web-based Tourist Resorts and Places Management Systems

Analyzing tourist data on Twitter: a case study in the province of Granada at Spain

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