Attitudes Expressed in Online Comments about Environmental Factors in the Tourism Sector: An Exploratory Study

Abstract

The object of this exploratory study is to identify the positive, neutral and negative environment factors that affect users who visit Spanish hotels in order to help the hotel managers decide how to improve the quality of the services provided. To carry out the research a Sentiment Analysis was initially performed, grouping the sample of tweets (n = 14459) according to the feelings shown and then a textual analysis was used to identify the key environment factors in these feelings using the qualitative analysis software Nvivo (QSR International, Melbourne, Australia). The results of the exploratory study present the key environment factors that affect the users experience when visiting hotels in Spain, such as actions that support local traditions and products, the maintenance of rural areas respecting the local environment and nature, or respecting air quality in the areas where hotels have facilities and offer services. The conclusions of the research can help hotels improve their services and the impact on the environment, as well as improving the visitors experience based on the positive, neutral and negative environment factors which the visitors themselves identified.

A Three-Stage method for Data Text Mining: Using UGC in Business Intelligence Analysis

“…SA aims to discover differentiated feedback using varied methodological approaches that focus on polarity, subject, and opinion holder [11]. In previous research, SA has been reported to be able to identify the sentiments about products [2,5,6]. Within SA techniques, text information can be tagged as pertaining to either of two categories: fact or opinion.…”

“…In this respect it is important to properly implement the proposed process and correctly filter the user-generated content. Appropriate practices include the following: (i) removing the duplicate content; (ii) accessing only public UGC; (iii) collecting the data that can be grouped or classified around a tag or topic, such as companies indexed in a ranking, companies that have won a prize, #hashtags, and so forth [2,5,7,19]. In this way, the dataset will be classified around a defined grouping [14,18].…”

“…Over the past decade several methodologies based on approximations to perform data analysis and obtain variables related to BI have been proposed [2,5,6], but in the present study a new three-stage methodological approach that covers a gap in previous research is laid out. In this new approach our first objective is to identify KIs and insights from large amounts of UGC data using three well defined discrete approaches (Latent Dirichlet Allocation (LDA), sentiment analysis (SA) and textual analysis (TA)).…”

Complexity in the Acceptance of Sustainable Search Engines on the Internet: An Analysis of Unobserved Heterogeneity with FIMIX‐PLS

“…PU is defined as how much an individual believes that using a particular system will improve their performance [32]. It is a measure of the subjective likelihood that a potential user will increase their work performance in an organization when using the technology [35]. The PEOU variable measures how much an individual believes that using a particular system is effort-free.…”

Exploring How Homophily and Accessibility Can Facilitate Polarization in Social Networks

“…Those outside yet accessible depend upon a parameter value that controls the probability that such a connection can occur and certain platforms change that probability. From the societal analogs described as example from where the facility to access non-local associates can arise from, examples such as Twitter communities, Rotary Clubs and others are mentioned (examples of this in real world scenarios are discussed in [15,16]). These aggregations of users provide a meeting place for the choice process of new friendships to occur outside of the pre-existing locality and provide the means for the accessibility but are not explicitly modeled.…”