Since social media has been growing rapidly, the restaurant industry has been exploring this area extensively. Given that social media provides restaurant consumers with an opportunity to share their dining experiences, several studies have examined the impact of social media on consumer restaurant selection (Tran, 2015). As a part of the social media umbrella, online reviews are significant factors that influence consumer restaurant selection (Park & Nicolau, 2015; Yang, Hlee, Lee, Koo, 2017). However, there is a lack of understanding with regard to which attributes of restaurant online reviews are the most influential when it comes to customer decision making. Therefore, this study aims to investigate the relative importance of online review attributes in consumer restaurant selection. Particularly, this study focuses on the number of online reviews, the overall restaurant rating, and the following restaurant attributes: food quality, service quality, atmosphere, and price, to address the purpose of the research. Based on the recommendation of Orme, (2010), 353 respondents are recruited via Amazon’s Mechanical Turk, and a choice-based-conjoint (CBC) analysis is performed. The CBC analysis reveals the relative importance of each attribute for customer decision making. Based on the CBC analysis, the results confirms that food quality is the most important attribute in consumer restaurant selection. This factor is followed by overall restaurant rating, price, service quality, the number of online reviews, and atmosphere. Additionally, the overall restaurant rating is determined to be a substantially important factor that influences consumer restaurant selection, while the rest of the attributes vary in their rank. The market simulation calculated the preference estimates for the products for each respondent. This approach predicts the impact of each attribute on the market share. Food quality and overall restaurant rating are used for the market simulations. Therefore, it is also found that in relation to the market simulation, the decrease of food quality influenced the market share by about 58.88%. The findings of this study contribute greatly to the knowledge of the importance of food quality, and as a result, an overall restaurant rating. Therefore, restaurant managers should prioritize these key attributes to manage strategies for the restaurant

This project examines user-generated health narratives through corpus analysis of 246 reviews posted on Midwestern Hospital’s Yelp page. Understanding how different stakeholders act and interact within online health communities models a shift in new conceptions of health, and provides evidence of health ecologies’ ability to determine patient perceptions of care. Documents produced by users in these health communities represent health narratives comprised of a user’s health experience, that user’s treatment perceptions, and the community’s perceptions of the user’s experience. Author uses corpus methods to interpret user trace data and rhetorical moves embedded in health narratives. Findings suggest that users who interact with the Yelp community produce different health narratives than less engaged users. Understanding how different stakeholders act and interact within online health communities models a shift in new conceptions of health, and provides evidence of health ecologies’ ability to determine patient perceptions of care.

The Internet has grown to become one of the most influential tools affecting the tourism industry. This study seeks to explore a smaller piece of a widely recognized phenomenon, breaking off to study the impacts of online reviews on TripAdvisor and electronic word-of-mouth in the hotel sector. The study further attempts to identify problems and advantages with the increased use of consumer generated media-sites. One of the main motivations for this study is also the lack of profound studies examining hotel responses to online reviews and destination impacts. The scope of this study is limited to examine three hotels and their respective reviews, on the Aland Islands. Thus this study does not necessarily seek to generalize results in other instances. The identified problem in this thesis is that hotel operators experience difficulties in managing what is being written about them as the perception of time and space changes, owing to the Internet. In making progress to this problem, the study was conducted through semi-structured interviews and a thematic analysis, to understand the specifics of the context. Furthermore, this methodology was used to understand the perspectives of the informants. The results indicate that online reviews on TripAdvisor follow specific themes and are considered an important source of information for hotel operators. However, there seems to be some limitations in management, due to lack of opportunities and strategic plans of actions in the hotel sector. There is, however, a collective understanding and willingness amongst hotels to further immerse themselves in the work of managing reviews.

Since 1991 government control of textbooks no longer takes place and the pedagogical framing is influenced by production relations in a rectified global mass culture where impressions and role models from the media have greater influence on students’ worldview and their socialization. Norms, ideas, values and attitudes are conveyed through language which is therefore seen as central in the creation of ideas about what is considered male or female. The purpose of the study is to examine, from a gender perspective, how girls/women and boys/men are portrayed and represented in both text and image in two textbooks in the subject of Swedish for kids in the third grade. Furthermore, the study aims to investigate the type of professions and/or activities occurring as masculine and feminine. The theories used for the analysis of the material are Yvonne Hirdman’s gender theory, Raewyn Connell's conception of gender relations and Bronwyn Davies sociological theory. The questions that are answered in the study are the following: * In what way is gender constructed in the representation of girls/women and boys/men by image and text in textbooks? * Which professions and/or activities are linked to masculinity and femininity? I have in my investigation concluded that boys/men and girls/women are represented differently in both textbooks. In the textbook ”LäsDax 3” I found that both genders are represented in a stereotypical way, while the other textbook “ABC-klubben, Nyckeln till skatten” is trying to move beyond the stereotypical representation. In the latter mentioned textbook, men and women are both allowed to exceed the prevailing genus contract of society by describing girls as active and men as emotional. Regarding professions and/or activities I could also find that they differ in the textbooks. ”LäsDax 3” follows the norms of society regarding what is seen as masculine or feminine, while “ABC-klubben, Nyckeln till skatten” exceeds society’s norms.

For this study, thirty book reviews in two fields, sixteen in history and sixteen in economics, written in Thai and English (eight in each discipline) were randomly collected from Thai and US academic journals in order to examine the moves in the overall structures of the reviews and reviewers' politeness strategies, and to consider the extend to which the texts vary across the two languages and whether the variation is present in both disciplines.

Word of Mouth (WOM) is an ancient concept that has been around since the uprising of markets. However, due to the increased internet usage a new form of WOM has emerged called Electronic Word of Mouth (eWOM). The concept of eWOM takes form when consumers communicate with each other or a company online. Consumers can communicate by sharing positive and negative comments about the experiences they have had with companies and products. These comments have a positive or negative effect on consumer satisfaction and a company's reputation. Due to this it is important for companies to communicate with their consumers online across various platforms. Companies can communicate with their consumers by responding to comments. An industry that frequently responds to consumers eWOM is the hotel industry. Hotel guests often write reviews and comments online that managers in the hotel industry respond to. However, hotels have visitors from all around the world and consumers from different cultures tend to engage in eWOM in different ways. This is important for hotels to be aware of. Hence, the purpose of this study is to gain a more profound understanding on how managers in the hotel industry respond to eWOM posted on social media and review sites by consumers from different cultures.   This study is a case study where two hotels located in northern Sweden have been interviewed. The interviewees of the two hotels are managers with a lot of experience of the hotel industry. The findings of the case study suggest that hotels respond to consumers' positive and negative eWOM. Positive comments are usually responded to with a personalized and appreciative response to increase consumer satisfaction. Negative comments are responded to by addressing the issue in order to make up for service failure. The study also found that hotels do not pay much attention to cultural differences and the reason for this is because most of the hotel’s consumers are from individualistic cultures.

This thesis explores the use of unstructured data, and specifically textual data, in providing consumer insights and improving business decisions. The thesis consists of two essays. In essay I, I examine how the linguistic similarity between the language used by reviewers of a product and a prospective customer’s own writing style can be leveraged to assess the match between customers and products. Applying tools from machine learning, Bayesian statistics, and computational linguistics to a large-scale dataset from Yelp, I find that the closer the writing style of a restaurant’s past reviews are to a prospective customer’s writing style, the more likely that customer is to write a review for that restaurant. This effect holds across restaurant types and is driven by the linguistic similarity between the customer’s own reviews and positive past reviews for the restaurant. Further, I find that similarity with respect to words related to leisure (e.g., family, wine, beer, weekend), biology (e.g., eat, life, love), as well as swear words are most influential in creating a match between customers and restaurants. In essay II, I examine whether borrowers consciously or not, leave traces of their intentions, circumstances, and personality traits in the text they write when applying for a loan. I find that this textual information has a substantial and significant ability to predict whether borrowers will pay back the loan above and beyond the financial and demographic variables commonly used in models predicting default. Using text-mining and machine-learning tools to automatically process and analyze the raw text in over 120 thousand loan requests from Prosper.com, an online crowdfunding platform, I find that including the textual information in the loan significantly helps predict loan default and can have substantial financial implications. I find that loan requests written by defaulting borrowers are more likely to include words related to their family, mentions of God, the borrower’s financial and general hardship, pleading lenders for help, and short-term focused words. I further observe that defaulting loan requests are written in a manner consistent with the writing style of extroverts and liars.

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Review helpfulness prediction has attracted growing attention of researchers that proposed various solutions using Machine Learning (ML) techniques. Most of the studies used online reviews from Amazon to predict helpfulness where each review is accompanied with information indicating how many people found the review helpful. This research aims to analyze the complete process of modelling review helpfulness from several perspectives. Experiments are conducted comparing different methods for representing the review text as well as analyzing the importance of data sampling for regression compared to using non-sampled datasets. Additionally, a set of review, review meta-data and product features are evaluated on their ability to capture the helpfulness of reviews. Two Amazon product review datasets are utilized for the experiments and two of the most widely used machine-learning algorithms, Linear Regression and Convolutional Neural Network (CNN). The experiments empirically demonstrate that the choice of representation of the textual data has an impact on performance with tf-idf and word2Vec obtaining the lowest Mean Squared Error (MSE) values. The importance of data sampling is also evident from the experiments as the imbalanced ratios in the unsampled dataset negatively affected the performance of both models with bias predictions in favor of the majority group of high ratios in the dataset. Lastly, the findings suggest that review features such as unigrams of review text and title, length of review text in words, polarity of title along with rating as review meta-data feature are the most influential features for determining helpfulness of reviews.

The purpose of this study is to research which factors influence consumer satisfaction towards a fashion company. The purpose is also, to contribute with knowledge on the concept Slow Fashion.