788 resultados para Online reviews
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The availability of the sheer volume of online product reviews makes it possible to derive implicit demographic information of product adopters from review documents. This paper proposes a novel approach to the extraction of product adopter mentions from online reviews. The extracted product adopters are the ncategorise into a number of different demographic user groups. The aggregated demographic information of many product adopters can be used to characterize both products and users, which can be incorporated into a recommendation method using weighted regularised matrix factorisation. Our experimental results on over 15 million reviews crawled from JINGDONG, the largest B2C e-commerce website in China, show the feasibility and effectiveness of our proposed frame work for product recommendation.
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We present in this article an automated framework that extracts product adopter information from online reviews and incorporates the extracted information into feature-based matrix factorization formore effective product recommendation. In specific, we propose a bootstrapping approach for the extraction of product adopters from review text and categorize them into a number of different demographic categories. The aggregated demographic information of many product adopters can be used to characterize both products and users in the form of distributions over different demographic categories. We further propose a graphbased method to iteratively update user- and product-related distributions more reliably in a heterogeneous user-product graph and incorporate them as features into the matrix factorization approach for product recommendation. Our experimental results on a large dataset crawled from JINGDONG, the largest B2C e-commerce website in China, show that our proposed framework outperforms a number of competitive baselines for product recommendation.
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In economics of information theory, credence products are those whose quality is difficult or impossible for consumers to assess, even after they have consumed the product (Darby & Karni, 1973). This dissertation is focused on the content, consumer perception, and power of online reviews for credence services. Economics of information theory has long assumed, without empirical confirmation, that consumers will discount the credibility of claims about credence quality attributes. The same theories predict that because credence services are by definition obscure to the consumer, reviews of credence services are incapable of signaling quality. Our research aims to question these assumptions. In the first essay we examine how the content and structure of online reviews of credence services systematically differ from the content and structure of reviews of experience services and how consumers judge these differences. We have found that online reviews of credence services have either less important or less credible content than reviews of experience services and that consumers do discount the credibility of credence claims. However, while consumers rationally discount the credibility of simple credence claims in a review, more complex argument structure and the inclusion of evidence attenuate this effect. In the second essay we ask, “Can online reviews predict the worst doctors?” We examine the power of online reviews to detect low quality, as measured by state medical board sanctions. We find that online reviews are somewhat predictive of a doctor’s suitability to practice medicine; however, not all the data are useful. Numerical or star ratings provide the strongest quality signal; user-submitted text provides some signal but is subsumed almost completely by ratings. Of the ratings variables in our dataset, we find that punctuality, rather than knowledge, is the strongest predictor of medical board sanctions. These results challenge the definition of credence products, which is a long-standing construct in economics of information theory. Our results also have implications for online review users, review platforms, and for the use of predictive modeling in the context of information systems research.
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The influence of positive online consumer reviews on a traveler's decision making remains unclear. To better understand the perceived usefulness of online reviews, this study conducts two experiments using positive and negative online consumer reviews. Study results suggest that high risk-averse travelers find negative online reviews more useful than positive reviews. For positive online reviews, high-risk averse travelers feel expert reviewers' postings, travel product pictures, and well-known brand names enhance usefulness of the positive online reviews. These findings offer interesting implications for both marketing theory and practice.
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Consumers tend to seek heuristic information cues to simplify the amount of information involved in tourist decisions. Accordingly, star ratings in online reviews are a critical heuristic element of the perceived evaluation of online consumer information. The objective of this article is to assess the effect of review ratings on usefulness and enjoyment. The empirical application is carried out on a sample of 5,090 reviews of 45 restaurants in London and New York. The results show that people perceive extreme ratings (positive or negative) as more useful and enjoyable than moderate ratings, giving rise to a U-shaped line, with asymmetric effects: the size of the effect of online reviews depends on whether they are positive or negative.
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Online third-party reviews have been grown over the last decade and they now play an important role as a tool for helping customers evaluate products and services that in many cases offer more than tangible features. This study intends to quantify the impact online ratings have over video game sales by conducting a linear regression analysis on 300 titles for the previous console generation (PlayStation® 3 and Xbox® 360) using a data from the video game industry to understand the existing influence on this particular market. The findings showed that these variables have a weak linear relationship thus suggesting that quality of a title explains little the commercial success of a video game and instead this should cover a wider range of factors. Afterwards, we compare results to previous ones and discuss the managerial implications for upcoming gaming generations.
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The nature tourism experienced a great expansion of its market with the appearance of different lifestyles. In this Work Project a study regarding the website direct sales of Rota Vicentina was developed. Its website shows the idea of being solely an information structure and not a purchase one, leading to a current absence of online sales. Hence, it is suggested the modification of its business model, using different instruments and channels. Some digital marketing recommendations were developed in order to boost website sales, such as a platform for online reviews, remarketing campaigns and social media activity.
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Founded and for many years edited by L. Asher and K. Spiro.
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BACKGROUND: Even though physician rating websites (PRWs) have been gaining in importance in both practice and research, little evidence is available on the association of patients' online ratings with the quality of care of physicians. It thus remains unclear whether patients should rely on these ratings when selecting a physician. The objective of this study was to measure the association between online ratings and structural and quality of care measures for 65 physician practices from the German Integrated Health Care Network "Quality and Efficiency" (QuE). METHODS: Online reviews from two German PRWs were included which covered a three-year period (2011 to 2013) and included 1179 and 991 ratings, respectively. Information for 65 QuE practices was obtained for the year 2012 and included 21 measures related to structural information (N = 6), process quality (N = 10), intermediate outcomes (N = 2), patient satisfaction (N = 1), and costs (N = 2). The Spearman rank coefficient of correlation was applied to measure the association between ratings and practice-related information. RESULTS: Patient satisfaction results from offline surveys and the patients per doctor ratio in a practice were shown to be significantly associated with online ratings on both PRWs. For one PRW, additional significant associations could be shown between online ratings and cost-related measures for medication, preventative examinations, and one diabetes type 2-related intermediate outcome measure. There again, results from the second PRW showed significant associations with the age of the physicians and the number of patients per practice, four process-related quality measures for diabetes type 2 and asthma, and one cost-related measure for medication. CONCLUSIONS: Several significant associations were found which varied between the PRWs. Patients interested in the satisfaction of other patients with a physician might select a physician on the basis of online ratings. Even though our results indicate associations with some diabetes and asthma measures, but not with coronary heart disease measures, there is still insufficient evidence to draw strong conclusions. The limited number of practices in our study may have weakened our findings.
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Com o rápido aumento da utilização da internet no mundo, os consumidores utilizam cada vez mais os websites para comparação, compra e venda de produtos. Atualmente os utilizadores da internet deixaram de procurar exclusivamente informação e tornaram-se eles próprios fornecedores de experiências através de comunidades online, que continuam em grande crescimento. Seguindo essa tendência, muitas indústrias escolheram a internet como canal de comunicação preferido e a indústria hoteleira não foge à regra. Assim a presente dissertação resulta numa pesquisa, em que o principal objetivo é entender de que forma os diversos fatores de informação presentes nos comentários online realizados nos websites de comparação de hotéis influenciam a utilização da informação pelo consumidor. Na presente metodologia é utilizado o modelo de Filieri e McLeay (2014), o tipo de inquérito utilizado é um questionário online para analisar quais os fatores que mais influenciam os consumidores a utilizarem a informação disponível nos comentários online. Os principais resultados obtidos neste estudo indicam que a precisão da informação, a consistência da informação e o ranking do alojamento influenciam a utilização da informação presente nos comentários online.
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This thesis examines the processes through which identity is acquired and the processes that Hollywood :films employ to facilitate audience identification in order to determine the extent to which individuality is possible within postmodem society. Opposing views of identity formation are considered: on the one hand, that of the Frankfurt School which envisions the mass audience controlled by the culture industry and on the other, that of John Fiske which places control in the hands of the individual. The thesis takes a mediating approach, conceding that while the mass media do provide and influence identity formation, individuals can and do decode a variety of meanings from the material made available to them in accordance with the text's use-value in relation to the individual's circumstances. The analysis conducted in this thesis operates on the assumption that audiences acquire identity components in exchange for paying to see a particular film. Reality Bites (Ben Stiller 1994) and Scream (Wes Craven 1996) are analyzed as examples of mainstream 1990s films whose material circumstances encourage audience identification and whose popularity suggest that audiences did indeed identify with them. The Royal Tenenbaums (Wes Anderson 2001) is considered for its art film sensibilities and is examined in order to determine to what extent this film can be considered a counter example. The analysis consists of a combination of textual analysis and reception study in an attempt to avoid the problems associated with each approach when employed alone. My interpretation of the filmmakers' and marketers' messages will be compared with online reviews posted by film viewers to determine how audiences received and made use of the material available to them. Viewer-posted reviews, both unsolicited and unrestricted, as found online, will be consulted and will represent a segment of the popular audience for the three films to be analyzed.
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Cette thèse est une collection de trois articles en économie de l'information. Le premier chapitre sert d'introduction et les Chapitres 2 à 4 constituent le coeur de l'ouvrage. Le Chapitre 2 porte sur l’acquisition d’information sur l’Internet par le biais d'avis de consommateurs. En particulier, je détermine si les avis laissés par les acheteurs peuvent tout de même transmettre de l’information à d’autres consommateurs, lorsqu’il est connu que les vendeurs peuvent publier de faux avis à propos de leurs produits. Afin de comprendre si cette manipulation des avis est problématique, je démontre que la plateforme sur laquelle les avis sont publiés (e.g. TripAdvisor, Yelp) est un tiers important à considérer, autant que les vendeurs tentant de falsifier les avis. En effet, le design adopté par la plateforme a un effet indirect sur le niveau de manipulation des vendeurs. En particulier, je démontre que la plateforme, en cachant une partie du contenu qu'elle détient sur les avis, peut parfois améliorer la qualité de l'information obtenue par les consommateurs. Finalement, le design qui est choisi par la plateforme peut être lié à la façon dont elle génère ses revenus. Je montre qu'une plateforme générant des revenus par le biais de commissions sur les ventes peut être plus tolérante à la manipulation qu'une plateforme qui génère des revenus par le biais de publicité. Le Chapitre 3 est écrit en collaboration avec Marc Santugini. Dans ce chapitre, nous étudions les effets de la discrimination par les prix au troisième degré en présence de consommateurs non informés qui apprennent sur la qualité d'un produit par le biais de son prix. Dans un environnement stochastique avec deux segments de marché, nous démontrons que la discrimination par les prix peut nuire à la firme et être bénéfique pour les consommateurs. D'un côté, la discrimination par les prix diminue l'incertitude à laquelle font face les consommateurs, c.-à-d., la variance des croyances postérieures est plus faible avec discrimination qu'avec un prix uniforme. En effet, le fait d'observer deux prix (avec discrimination) procure plus d'information aux consommateurs, et ce, même si individuellement chacun de ces prix est moins informatif que le prix uniforme. De l'autre côté, il n'est pas toujours optimal pour la firme de faire de la discrimination par les prix puisque la présence de consommateurs non informés lui donne une incitation à s'engager dans du signaling. Si l'avantage procuré par la flexibilité de fixer deux prix différents est contrebalancé par le coût du signaling avec deux prix différents, alors il est optimal pour la firme de fixer un prix uniforme sur le marché. Finalement, le Chapitre 4 est écrit en collaboration avec Sidartha Gordon. Dans ce chapitre, nous étudions une classe de jeux où les joueurs sont contraints dans le nombre de sources d'information qu'ils peuvent choisir pour apprendre sur un paramètre du jeu, mais où ils ont une certaine liberté quant au degré de dépendance de leurs signaux, avant de prendre une action. En introduisant un nouvel ordre de dépendance entre signaux, nous démontrons qu'un joueur préfère de l'information qui est la plus dépendante possible de l'information obtenue par les joueurs pour qui les actions sont soit, compléments stratégiques et isotoniques, soit substituts stratégiques et anti-toniques, avec la sienne. De même, un joueur préfère de l'information qui est la moins dépendante possible de l'information obtenue par les joueurs pour qui les actions sont soit, substituts stratégiques et isotoniques, soit compléments stratégiques et anti-toniques, avec la sienne. Nous établissons également des conditions suffisantes pour qu'une structure d'information donnée, information publique ou privée par exemple, soit possible à l'équilibre.
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Product recommender systems are often deployed by e-commerce websites to improve user experience and increase sales. However, recommendation is limited by the product information hosted in those e-commerce sites and is only triggered when users are performing e-commerce activities. In this paper, we develop a novel product recommender system called METIS, a MErchanT Intelligence recommender System, which detects users' purchase intents from their microblogs in near real-time and makes product recommendation based on matching the users' demographic information extracted from their public profiles with product demographics learned from microblogs and online reviews. METIS distinguishes itself from traditional product recommender systems in the following aspects: 1) METIS was developed based on a microblogging service platform. As such, it is not limited by the information available in any specific e-commerce website. In addition, METIS is able to track users' purchase intents in near real-time and make recommendations accordingly. 2) In METIS, product recommendation is framed as a learning to rank problem. Users' characteristics extracted from their public profiles in microblogs and products' demographics learned from both online product reviews and microblogs are fed into learning to rank algorithms for product recommendation. We have evaluated our system in a large dataset crawled from Sina Weibo. The experimental results have verified the feasibility and effectiveness of our system. We have also made a demo version of our system publicly available and have implemented a live system which allows registered users to receive recommendations in real time. © 2014 ACM.
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The growing availability and popularity of opinion rich resources on the online web resources, such as review sites and personal blogs, has made it convenient to find out about the opinions and experiences of layman people. But, simultaneously, this huge eruption of data has made it difficult to reach to a conclusion. In this thesis, I develop a novel recommendation system, Recomendr that can help users digest all the reviews about an entity and compare candidate entities based on ad-hoc dimensions specified by keywords. It expects keyword specified ad-hoc dimensions/features as input from the user and based on those features; it compares the selected range of entities using reviews provided on the related User Generated Contents (UGC) e.g. online reviews. It then rates the textual stream of data using a scoring function and returns the decision based on an aggregate opinion to the user. Evaluation of Recomendr using a data set in the laptop domain shows that it can effectively recommend the best laptop as per user-specified dimensions such as price. Recomendr is a general system that can potentially work for any entities on which online reviews or opinionated text is available.