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This research is to identify how user-generated contents (UGC) affect a pre-trip decision on the booking of a guesthouse among international travelers. Online surveys are conducted among social network users who have booked an ecolodge in the past year. A snowball sampling is used, which posts a questionnaire link in social networks including Twitter, Facebook, and Instagram in addition to travel blogs. This study indicates a positive relationship between UGC and lodging selection. UGC is considered as a significant predictor of booking an environmentally friendly guesthouse. Among the UGCs, travelers' review is the most important one influencing guesthouse selection. Future studies may focus on other IT potentials such as “Gamification” or other types of content such as “Podcasts” or “live videos” to engage independent travelers.

Purpose — The purpose of this study is to describe the development of contents, visibility and use of two Library 2.0 services, Häme-Wiki and the Virtual Path map service, launched by Hämeenlinna City Library and based on crowdsourcing, service convergence and the application on Web 2.0 technology.

Design/methodology/approach — The development of the contents of the services were analysed by observing the increase in articles and other items published in them. The interest in these sites and their use were studied by the number of their contributors, users and downloads and by link analysis concerning inbound links. To gather users’ experiences, a Web survey was directed to the registered users by e-mail. A questionnaire for all users was linked to the front page of both services. Qualitative theme interviews were conducted with the staff of Hämeenlinna City Library to elicit their experiences concerning the use of the services and their impact on the work community.

Findings — The reception of the services was evidenced by the daily increasing number of published articles and maps, also indicating crowdsourcing. Their use was clearly described by the increasing download figures and inbound links. Both services offered users information not available elsewhere.

The study is limited by the low number of responses in the Web surveys.

Practical implications — Practical implications originate from the concrete examples of content sharing, crowdsourcing and service convergence which have not been much studied in library context.

Originality/value — The practical implications of the work also contribute to the value of the paper for developers of Web 2.0 services and service convergence.

This chapter outlines how search engine technology can be used in online public access catalogs (OPACs) to help improve users’ experiences, to identify users’ intentions, and to indicate how it can be applied in the library context, along with how sophisticated ranking criteria can be applied to the online library catalog. A review of the literature and the current OPAC developments forms the basis of recommendations on how to improve OPACs. Findings were that the major shortcomings of current OPACs are that they are not sufficiently user-centered and that their results presentations lack sophistication. Furthermore, these shortcomings are not addressed in current 2.0 developments. It is argued that OPAC development should be made search-centered before additional features are applied. Although the recommendations on ranking functionality and the use of user intentions are only conceptual and not yet applied to a library catalogue, practitioners will find recommendations for developing better OPACs in this chapter. In short, readers will find a systematic view on how the search engines’ strengths can be applied to improving libraries’ online catalogs.

There is no doubt that social media have had a powerful impact on the way people experience the world around them. People love sharing new experiences and telling social networks about upcoming travel plans and reminiscing about them after they have returned. People prefer to buy products and services from brands they trust. Social media allow people to share written testaments to the brand's most amazing qualities, and share pictures and videos of their experiences. Social media make it easy to approach the enterprises and interact with them.

Connecting reputation management and social media is the process of monitoring and handling user-generated social media content such as reviews to impact the way a company is recognized. Tangible aspects of services and products are evaluated by customers of tourism and hospitality enterprises in an individual manner, and relevant opinions are shared on various social media platforms. The cost of a negative experience is rather high – the “eWOM” (electronic word-of-mouth) through social media essentially could destroy a business. For many businesses, a bad review or comment on one social networking site could spread to other social media tools.

The pattern of use of social media by customers of tourism and hospitality organizations can be divided into three stages: pretrip, during the trip, and posttrip use of social media. Customer experiences during each of these stages can be reflected on different social media networks. The manner of the use of social media by customers at all three stages could influence on performances of tourism and hospitality organizations as advantages and challenges. In this article authors are discussing both positive and negative impacts depending on consumer experiences and a range of other factors. Social media implementing blogs, social networking sites, photo and video stories, chats, forums, and other forms of communication need to be used by management of tourism and hospitality enterprises in an integrated manner. Great opportunities offered by viral marketing are fully appreciated and acted upon by managers of hospitality organizations.

It is important for the enterprise to develop an engaged audience by creating and sharing relevant content on social platforms. In addition to relevant content it is important to pay attention to interacting with the audience. Focus must be on products and services, but without interacting and engaging with the audience the enterprise might lose them. Social media are an option for tourism and hospitality to get the opportunity to control and present their contents including their products and services, and using it positively, solve their core values and draw and retain back their customers. Using social media channels can help enterprises to generate more profit. Setting special procedures or documents on how to respond to negative and positive comments guarantees correct and consistent execution. In this chapter the reader could find some real examples from tourism and hospitality enterprises.

Online reputation manager has become increasingly important in tourism industry. Managers, regardless of working for a hospitality structure or a tourism destination, are paying more and more attention in respect of the importance of reputational levels. Online reputation, in fact, originates in visitor's user-generated contents (UGCs) but reverberates on the whole web, on successive visitors' attitude and behavior, and on managed organization performances. How to manage online reputation in tourism and destination management anyway mostly stayed an anecdotal topic for many years. While best practices exist, indeed, literature has frequently neglected their systematization. Building on this need, this book will try to improve and organize the existing body of knowledge on this topic to help future hotel and destination managers to better deal with the mounting environmental complexity.

The chapter proposes to investigate online reputation of hospitality brands and its measurements. Brand reputation is generally defined as an overall appraisal of a company by its stakeholders, which is the result of the company's past actions and predictions about the company's future (Ferguson, Deephouse, & Ferguson, 2000). Being viewed as the opinion shared among a group of stakeholders (Dowling, 2008), it plays an important role in the tourism industry. With the progress of Information Communication Technologies (ICTs), reviews and user-generated contents of destinations and of hospitality companies together with the related emerging brand reputation can influence consumers' behaviors and choices. Brand reputation analysis could be more useful in the hospitality brand management when integrated with brand image and brand identity analysis, mainly because in tourism businesses and destinations, brands are typically affected by an inherent fragility determined by the service nature of products (Casarin, 1996). According to Biel (1991), the meanings that consumers assign to a brand are synthesized into brand associations formed by the components perceived to underlie the brand's image. As well as brand reputation, strong, positive and unique associations reinforce a brand and increase its equity that requires significant internal brand identity efforts, which should create a corresponding brand image through integration in overall marketing programmes (Keller, 2003). It makes sense to develop an analytical research approach that compares online brand reputation (OBR) with brand association matching as a measure of the alignment between brand identity and brand image in hospitality companies. This comparative analysis emerging from brand reputation, brand image and brand identity analysis can reveal divergent situations (i.e., high brand reputation and low brand association matching) and orient brand managers in reviewing online brand communication. Brand reputation and brand image analysis will be contextualized in an online community as a social setting that is considered to be a new type of market (Muniz & O'Guinn, 2001). We focus on hospitality online communities populated by consumers and other actors such as influencers and bloggers: their brand perception could be separately compared with brand identity that we will extract from company communications including presentational information and brand-related press releases found on websites, nonfinancial narrative from annual reports, and interviews with managers published in mainstream media sources. In our analysis we will focalize on a cluster of luxury hospitality companies integrating a netnographic and text-mining techniques. We will use both the techniques in order to (1) extract and study brand associations in terms of brand reputation, brand image, and brand identity; (2) develop indicators of brand reputation and brand association matching; and (3) discuss their utility in the management of the hospitality company brands.

This chapter investigates the behavior of Reddit’s news subreddit users and the relationship between their sentiment on exchange rates. Using graphical models and natural language processing, hidden online communities among Reddit users are discovered. The data set used in this project is a mixture of text and categorical data from Reddit’s news subreddit. These data include the titles of the news pages, as well as a few user characteristics, in addition to users’ comments. This data set is an excellent resource to study user reaction to news since their comments are directly linked to the webpage contents. The model considered in this chapter is a hierarchical mixture model which is a generative model that detects overlapping networks using the sentiment from the user generated content. The advantage of this model is that the communities (or groups) are assumed to follow a Chinese restaurant process, and therefore it can automatically detect and cluster the communities. The hidden variables and the hyperparameters for this model are obtained using Gibbs sampling.

This chapter explores the ethical complexities of researching location-aware social discovery Smartphone applications (apps) and how they mediate contemporary experiences of travel. We highlight the context-specific approach required to carrying out research on Tinder, a location-aware app that enables people to connect with others in close proximity to them. By journeying through the early stages of our research project, we demonstrate how ethical considerations and dilemmas began long before our project became a project. We discuss the pulls toward data extraction/mining of user-generated content (i.e., Tinder user profiles) within digital social research and the ethical challenges of using this data for research purposes. We focus particularly on issues of informed consent, privacy, and copyright, and the differences between manual and automated data mining/extraction techniques. Excerpts from our university ethics application are included to demonstrate how our research sits uneasily within standardized ethical protocols. Our moves away from a ‘big data’ approach to more ‘traditional’ and participatory methodologies are located within questions of epistemology and ontology including our commitment to practicing a feminist research ethic. Our chapter concludes with the lessons learned in the aim to push forward with research in challenging online spaces and with new data sources.