10,746 research outputs found

    A comparative study of Bayesian models for unsupervised sentiment detection

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    This paper presents a comparative study of three closely related Bayesian models for unsupervised document level sentiment classification, namely, the latent sentiment model (LSM), the joint sentimenttopic (JST) model, and the Reverse-JST model. Extensive experiments have been conducted on two corpora, the movie review dataset and the multi-domain sentiment dataset. It has been found that while all the three models achieve either better or comparable performance on these two corpora when compared to the existing unsupervised sentiment classification approaches, both JST and Reverse-JST are able to extract sentiment-oriented topics. In addition, Reverse-JST always performs worse than JST suggesting that the JST model is more appropriate for joint sentiment topic detection

    Unraveling e-WOM patterns using text mining and sentiment analysis

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    Electronic word-of-mouth (e-WOM) is a very important way for firms to measure the pulse of its online reputation. Today, consumers use e-WOM as a way to interact with companies and share not only their satisfaction with the experience, but also their discontent. E-WOM is even a good way for companies to co-create better experiences that meet consumer needs. However, not many companies are using such unstructured information as a valuable resource to help in decision making. First, because e-WOM is mainly textual information that needs special data treatment and second, because it is spread in many different platforms and occurs in near-real-time, which makes it hard to handle. The current chapter revises the main methodologies used successfully to unravel hidden patterns in e-WOM in order to help decision makers to use such information to better align their companies with the consumer’s needs.info:eu-repo/semantics/acceptedVersio

    Word of Mouth, the Importance of Reviews and Ratings in Tourism Marketing

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    The Internet and social media have given place to what is commonly known as the democratization of content and this phenomenon is changing the way that consumers and companies interact. Business strategies are shifting from influencing consumers directly and induce sales to mediating the influence that Internet users have on each other. A consumer review is “a mixture of fact and opinion, impression and sentiment, found and unfound tidbits, experiences, and even rumor” (Blackshaw & Nazarro, 2006). Consumers' comments are seen as honest and transparent, but it is their subjective perception what shapes the behavior of other potential consumers. With the emergence of the Internet, tourists search for information and reviews of destinations, hotels or services. Several studies have highlighted the great influence of online reputation through reviews and ratings and how it affects purchasing decisions by others (Schuckert, Liu, & Law, 2015). These reviews are seen as unbiased and trustworthy, and considered to reduce uncertainty and perceived risks (Gretzel & Yoo, 2008; Park & Nicolau, 2015). Before choosing a destination, tourists are likely to spend a significant amount of time searching for information including reviews of other tourists posted on the Internet. The average traveler browses 38 websites prior to purchasing vacation packages (Schaal, 2013), which may include tourism forums, online reviews in booking sites and other generic social media websites such as Facebook and Twitter.Peer reviewedFinal Accepted Versio

    STUDY OF FIXED DOSE COMBINATIONS IN A TERTIARY CARE HOSPITAL

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    ABSTRACTObjective: To study and analyze the pattern of fixed dose combinations (FDCs) in medicine outpatient clinic.Methods: The study is prospective cross-sectional study was conducted for 2 months in medicine outpatient clinic in tertiary care hospital. Aftertaking approval from Institutional Ethics Committee, the data were collected on every working day of the hospital. Prescriptions from the patientscoming to medicine outpatient clinic outpatient department were taken and required information is filled in data record form.Results: A total of 83 prescriptions were included in the study. Out of 287 drugs, 111, i.e., 39.92% were fixed dose formulations. As per drug categoryanalysis, nutritional supplements were used (47.74%). While 27.02% and 9.03% of FDCs were given for cardiovascular complains and respiratorycomplains, respectively. FDCs used for other conditions were 16.21%. About 29.72% of total FDCs are included in approved list of FDCs by DrugsController General of India (DCGI), November 2014.Conclusion: 39.92% drugs are FDCs out of total prescribed drugs. Nutritional supplements are prescribed in higher concentrations. Out of total FDCsonly 29.72% were included in DCGI approved list of FDCs and only four FDCs are found in the WHO list of essential drugs.Keywords: Fixed dose combinations, Prescriptions, Approved, Drugs Controller General of India

    Developing App from User Feedback using Deep Learning

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    Barriers to the Export of Greek Wine

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    Although Greek wine is a high quality product, it is not well known in the international marketplace and it has not a recognised brand name. The aim of the current research is to examine the barriers to the export of Greek wine. In-depth Personal interviews were undertaken with producers, managers and people involved in the Greek wine industry. Participants provided information about the current situation and their projections about future. This research is based on qualitative methods. According to the results of the research the barriers could be separated into three basic categories, logistic and financial barriers, marketing and promotion barriers and policy barriers. This research offers Greek wine export managers and people involved in wine industry in general a possible mean of evaluating the marketing potentials of Greek wine in the international marketplace. It also helps Greek wine export managers to identify and recognise the problems that their product face in the international market, in order to improve its image, to conduct a brand building strategy and as a result to increase the exports.Greek wine, Marketing, Barriers, Exports, Agricultural and Food Policy, Food Consumption/Nutrition/Food Safety,
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