34 research outputs found

    The impact of social influence on the perceived helpfulness of online consumer reviews

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    Purpose This study aims to study to what extent the helpfulness votes others attach to a review affect a consumer's perceived helpfulness of that review. In addition, the purpose of this study is to investigate whether this social influence moderates the relationships among several content presentation factors and perceived helpfulness. Design/methodology/approach A choice-based conjoint experiment was carried out in which 201 respondents evaluated different reviews and chose the review they perceive as most helpful. Findings Consumers perceive reviews as more (less) helpful in the presence of clearly valenced positive (negative) helpfulness votes. In addition, helpfulness votes of others diminish the positive impact of structure and the negative impact of spelling errors. Research limitations/implications The experimental setup may limit the external validity of the study. Practical implications Providing a helpfulness button gives firms an instrument to offer content that consumers perceive as more useful and to exert some influence on the effects of content presentation factors on the review's helpfulness. Social implications Consumers tend to follow other consumers' opinions without forming their own opinion. Firms could misuse this tendency by hiring people to vote on reviews that are not necessarily helpful for consumers, but are helpful for the firm. Originality/value This study is the first to assess the extent to which social influence affects consumers' evaluation of reviews. Given that consumers use helpfulness votes to distinguish reviews, it is important to understand to what extent these votes reflect the actual helpfulness of the information in the review and to what extent they reflect previous helpfulness votes

    How TripAdvisor’s reviewers level of expertise influence their online rating behaviour and the usefulness of reviews

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    The internet has improved the buying behaviour of customers. The development of technologies has led to the dissemination of opinions on social networks where customers buy goods and services. These comments on social networks started to be a part of the purchasing process. Until a few years ago, customers used to choose their itineraries based on tourist guides or brochures. Nowadays, customers’ reviews have changed the way a destination is portrayed, enhancing the description of a product or a service to a level that not even the supplier was able to reach before. There are different types of reviewers. The aim of this study is to identify both reviews, experts and non-expert reviewers and analyse the way they write their reviews. Reviews of five hotels taken from the TripAdvisor website were used in order to conduct this study. After analyzing a great set of variables, the results show that there is not much different on the amount of positive/negative reviews written by a reviewer, however, there is a difference in the deeper meaning of a review when it is positive than when it is negative. The expert reviewer tends to be more emotional when writing positive reviews than negative reviews. Regarding the usefulness of the reviews, there is no significant difference in usefulness of a review whether is an written by an expert reviewer or by a non-expert reviewer. The results also indicate that being an expert does not influence the rating a reviewer gives to a hotel stay either. The study was conducted by using Lexalytics program to analyze a Natural Language Processing (NLP) used to classify reviews according to their polarity. With this study, a new research in study was filled. This study gives insights on the polarity of a review depending on the type of reviewer. The results of this study are also important for hotel managers in order for them to understand the type of guest in house.O desenvolvimento da tecnologia, com ênfase na internet e nos seus desenvolvimentos ao longo dos anos, melhorou o comportamento dos clientes e levou à disseminação de opiniões em redes sociais onde os clientes compram productos e serviços. Os comentários feitos a um produto ou serviço nas redes sociais começaram a fazer parte do processo da compra. Até há uns anos atrás, os clientes escolhiam os itinerários para as suas viagens com base em guias turísticos e brochuras. Recentemente, os comentários de clientes mudaram a maneira que um destino é explicado e ilustrado, melhorando, desta forma, a descrição de um produto/serviço a um nível que nem mesmo os fornecedores destes tinham alcançado ainda. Há diferentes tipos de reviewers. O objectivo deste estudo é identificar ambos tipos, expert e non-expert e analisar o estilo de reviews escrita por estes. Experts são assim denominados se tiverem escrito mais de dez reviews; por outro lado os non-expert reviewers são assim denominados se tiverem escrito menos de 10 reviews. Para este estudo, foi utilizada informação de cinco hotéis de Orlando, Florida, retirada do TripAdvisor. Depois de uma análise das variáveis, os resultados mostram que não há grande diferença no que toca ao volume de comentários positivos/negativos escritos por um utilizador. Por outro lado, existe uma diferença na emoção dada a cada comentário, entre os utilizadores. O expert reviewer tende a ser mais emocional quando escreve comentários positivos do que quando escreve comentários negativos. Relativamente a utilidade de cada comentário, não há grande diferença no que toca a ser um expert reviewer ou um non-expert a escrever um comentário. Os resultados indicam, também, que ser um expert não tem qualquer influência na avaliação que um utilizador dá a sua estadia num hotel. Este estudo foi feito com base no programa Lexalytics, com objectivo de analisar a Natural Language Processing (NLP) usada para classificar os comentários de acordo com a sua polaridade

    Proceedings der 11. Internationalen Tagung Wirtschaftsinformatik (WI2013) - Band 1

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    The two volumes represent the proceedings of the 11th International Conference on Wirtschaftsinformatik WI2013 (Business Information Systems). They include 118 papers from ten research tracks, a general track and the Student Consortium. The selection of all submissions was subject to a double blind procedure with three reviews for each paper and an overall acceptance rate of 25 percent. The WI2013 was organized at the University of Leipzig between February 27th and March 1st, 2013 and followed the main themes Innovation, Integration and Individualization.:Track 1: Individualization and Consumerization Track 2: Integrated Systems in Manufacturing Industries Track 3: Integrated Systems in Service Industries Track 4: Innovations and Business Models Track 5: Information and Knowledge ManagementDie zweibändigen Tagungsbände zur 11. Internationalen Tagung Wirtschaftsinformatik (WI2013) enthalten 118 Forschungsbeiträge aus zehn thematischen Tracks der Wirtschaftsinformatik, einem General Track sowie einem Student Consortium. Die Selektion der Artikel erfolgte nach einem Double-Blind-Verfahren mit jeweils drei Gutachten und führte zu einer Annahmequote von 25%. Die WI2013 hat vom 27.02. - 01.03.2013 unter den Leitthemen Innovation, Integration und Individualisierung an der Universität Leipzig stattgefunden.:Track 1: Individualization and Consumerization Track 2: Integrated Systems in Manufacturing Industries Track 3: Integrated Systems in Service Industries Track 4: Innovations and Business Models Track 5: Information and Knowledge Managemen

    Topic Modeling with Structured Priors for Text-Driven Science

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    Many scientific disciplines are being revolutionized by the explosion of public data on the web and social media, particularly in health and social sciences. For instance, by analyzing social media messages, we can instantly measure public opinion, understand population behaviors, and monitor events such as disease outbreaks and natural disasters. Taking advantage of these data sources requires tools that can make sense of massive amounts of unstructured and unlabeled text. Topic models, statistical models that posit low-dimensional representations of data, can uncover interesting latent structure in large text datasets and are popular tools for automatically identifying prominent themes in text. For example, prominent themes of discussion in social media might include politics and health. To be useful in scientific analyses, topic models must learn interpretable patterns that accurately correspond to real-world concepts of interest. This thesis will introduce topic models that can encode additional structures such as factorizations, hierarchies, and correlations of topics, and can incorporate supervision and domain knowledge. For example, topics about elections and Congressional legislation are related to each other (as part of a broader topic of “politics”), and certain political topics have partisan associations. These types of relations between topics can be modeled by formulating the Bayesian priors over parameters as functions of underlying “components,” which can be constrained in various ways to induce different structures. This approach is first introduced through a topic model called factorial LDA, which models a factorized structure in which topics are conceptually arranged in multiple dimensions. Factorial LDA can be used to model multiple types of information, for example topic and political ideology. We then introduce a family of structured-prior topic models called SPRITE, which creates a unifying representation that generalizes factorial LDA as well as other existing topic models, and creates a powerful framework for building new models. This thesis will also show how these topic models can be used in various scientific applications, such as extracting medical information from forums, measuring healthcare quality from patient reviews, and monitoring public opinion in social media

    Buyer beware : consumer response to manipulations of online product reviews

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    Online product reviews have become an important and influential source of information for consumers. Firms often manipulate online product reviews to influence consumer perceptions about the product, making it a research topic of urgent need for theory development and empirical investigation. In this thesis, we examine how consumers perceive and respond to the three commonly used manipulation tactics. Firstly, an exploratory pre-study via in-depth interviews with online shoppers indicates that consumers commonly have the knowledge for online review manipulations as well as for detecting them. In the first study, a survey was used to investigate the three popular manipulation tactics in terms of ethicality and deceptiveness. They rated hiding/deleting unfavorable messages as the most deceptive and unethical, followed by anonymously adding positive messages, and then offering incentives for posting favorable messages. In study 2, in a simulated field experiment, we introduce persuasion knowledge to further examine the negative influence of review manipulations on consumers’ attitudes. The results suggest that review manipulation increases suspicion of manipulations but can hardly reduce purchase intention of focal products. We also find that consumers’ persuasion knowledge enhances suspicion of manipulation, but lessens the negative impact of suspicion on purchase intention. The third study uses secondary data of a branded e-retailer and its third party website to cross-validate the effect of manipulations on product sales. The results confirm our hypotheses that review manipulation are effective in promoting sales; however, this influence would decrease over time. This research contributes to the online marketing literature by augmenting the Information Manipulation Theory and Persuasion Knowledge Model to examine the deceptive persuasion in the online context and its impact on consumer behavior. Furthermore, we also contribute to the literature of online WOM by empirically examining the influence of review manipulations on sales. Our findings provide valuable insights to practitioners and policy makers on the pitfalls of online manipulation activities and the need to ensure the healthy development of e-commerce

    Beyond maternal death: improving the quality of maternal care through national studies of ‘near-miss’ maternal morbidity

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    Knight M, Acosta C, Brocklehurst P, Cheshire A, Fitzpatrick K, Hinton L, Jokinen M, Kemp B, Kurinczuk JJ, Lewis G, Lindquist A, Locock L, Nair M, Patel N, Quigley M, Ridge D, Rivero-Arias O, Sellers S, Shah A on behalf of the UKNeS coapplicant group. Background Studies of maternal mortality have been shown to result in important improvements to women’s health. It is now recognised that in countries such as the UK, where maternal deaths are rare, the study of near-miss severe maternal morbidity provides additional information to aid disease prevention, treatment and service provision. Objectives To (1) estimate the incidence of specific near-miss morbidities; (2) assess the contribution of existing risk factors to incidence; (3) describe different interventions and their impact on outcomes and costs; (4) identify any groups in which outcomes differ; (5) investigate factors associated with maternal death; (6) compare an external confidential enquiry or a local review approach for investigating quality of care for affected women; and (7) assess the longer-term impacts. Methods Mixed quantitative and qualitative methods including primary national observational studies, database analyses, surveys and case studies overseen by a user advisory group. Setting Maternity units in all four countries of the UK. Participants Women with near-miss maternal morbidities, their partners and comparison women without severe morbidity. Main outcome measures The incidence, risk factors, management and outcomes of uterine rupture, placenta accreta, haemolysis, elevated liver enzymes and low platelets (HELLP) syndrome, severe sepsis, amniotic fluid embolism and pregnancy at advanced maternal age (≥ 48 years at completion of pregnancy); factors associated with progression from severe morbidity to death; associations between severe maternal morbidity and ethnicity and socioeconomic status; lessons for care identified by local and external review; economic evaluation of interventions for management of postpartum haemorrhage (PPH); women’s experiences of near-miss maternal morbidity; long-term outcomes; and models of maternity care commissioned through experience-led and standard approaches. Results Women and their partners reported long-term impacts of near-miss maternal morbidities on their physical and mental health. Older maternal age and caesarean delivery are associated with severe maternal morbidity in both current and future pregnancies. Antibiotic prescription for pregnant or postpartum women with suspected infection does not necessarily prevent progression to severe sepsis, which may be rapidly progressive. Delay in delivery, of up to 48 hours, may be safely undertaken in women with HELLP syndrome in whom there is no fetal compromise. Uterine compression sutures are a cost-effective second-line therapy for PPH. Medical comorbidities are associated with a fivefold increase in the odds of maternal death from direct pregnancy complications. External reviews identified more specific clinical messages for care than local reviews. Experience-led commissioning may be used as a way to commission maternity services. Limitations This programme used observational studies, some with limited sample size, and the possibility of uncontrolled confounding cannot be excluded. Conclusions Implementation of the findings of this research could prevent both future severe pregnancy complications as well as improving the outcome of pregnancy for women. One of the clearest findings relates to the population of women with other medical and mental health problems in pregnancy and their risk of severe morbidity. Further research into models of pre-pregnancy, pregnancy and postnatal care is clearly needed

    Beyond maternal death: improving the quality of maternal care through national studies of ‘near-miss’ maternal morbidity

    Get PDF
    BACKGROUND: Studies of maternal mortality have been shown to result in important improvements to women’s health. It is now recognised that in countries such as the UK, where maternal deaths are rare, the study of near-miss severe maternal morbidity provides additional information to aid disease prevention, treatment and service provision. OBJECTIVES: To (1) estimate the incidence of specific near-miss morbidities; (2) assess the contribution of existing risk factors to incidence; (3) describe different interventions and their impact on outcomes and costs; (4) identify any groups in which outcomes differ; (5) investigate factors associated with maternal death; (6) compare an external confidential enquiry or a local review approach for investigating quality of care for affected women; and (7) assess the longer-term impacts. METHODS: Mixed quantitative and qualitative methods including primary national observational studies, database analyses, surveys and case studies overseen by a user advisory group. SETTING: Maternity units in all four countries of the UK. PARTICIPANTS: Women with near-miss maternal morbidities, their partners and comparison women without severe morbidity. MAIN OUTCOME MEASURES: The incidence, risk factors, management and outcomes of uterine rupture, placenta accreta, haemolysis, elevated liver enzymes and low platelets (HELLP) syndrome, severe sepsis, amniotic fluid embolism and pregnancy at advanced maternal age (≥ 48 years at completion of pregnancy); factors associated with progression from severe morbidity to death; associations between severe maternal morbidity and ethnicity and socioeconomic status; lessons for care identified by local and external review; economic evaluation of interventions for management of postpartum haemorrhage (PPH); women’s experiences of near-miss maternal morbidity; long-term outcomes; and models of maternity care commissioned through experience-led and standard approaches. RESULTS: Women and their partners reported long-term impacts of near-miss maternal morbidities on their physical and mental health. Older maternal age and caesarean delivery are associated with severe maternal morbidity in both current and future pregnancies. Antibiotic prescription for pregnant or postpartum women with suspected infection does not necessarily prevent progression to severe sepsis, which may be rapidly progressive. Delay in delivery, of up to 48 hours, may be safely undertaken in women with HELLP syndrome in whom there is no fetal compromise. Uterine compression sutures are a cost effective second-line therapy for PPH. Medical comorbidities are associated with a fivefold increase in the odds of maternal death from direct pregnancy complications. External reviews identified more specific clinical messages for care than local reviews. Experience-led commissioning may be used as a way to commission maternity services. LIMITATIONS: This programme used observational studies, some with limited sample size, and the possibility of uncontrolled confounding cannot be excluded. CONCLUSIONS: Implementation of the findings of this research could prevent both future severe pregnancy complications as well as improving the outcome of pregnancy for women. One of the clearest findings relates to the population of women with other medical and mental health problems in pregnancy and their risk of severe morbidity. Further research into models of pre-pregnancy, pregnancy and postnatal care is clearly needed

    Automated telephone communication systems for preventive healthcare and management of long-term conditions

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    Background Automated telephone communication systems (ATCS) can deliver voice messages and collect health-related information from patients using either their telephone’s touch-tone keypad or voice recognition software. ATCS can supplement or replace telephone contact between health professionals and patients. There are four different types of ATCS: unidirectional (one-way, non-interactive voice communication), interactive voice response (IVR) systems, ATCS with additional functions such as access to an expert to request advice (ATCS Plus) and multimodal ATCS, where the calls are delivered as part of a multicomponent intervention. Objectives To assess the effects of ATCS for preventing disease and managing long-term conditions on behavioural change, clinical, process, cognitive, patient-centred and adverse outcomes. Search methods We searched 10 electronic databases (the Cochrane Central Register of Controlled Trials; MEDLINE; Embase; PsycINFO; CINAHL; Global Health; WHOLIS; LILACS; Web of Science; and ASSIA); three grey literature sources (Dissertation Abstracts, Index to Theses, Australasian Digital Theses); and two trial registries (www.controlled-trials.com; www.clinicaltrials.gov) for papers published between 1980 and June 2015. Selection criteria Randomised, cluster- and quasi-randomised trials, interrupted time series and controlled before-and-after studies comparing ATCS interventions, with any control or another ATCS type were eligible for inclusion. Studies in all settings, for all consumers/carers, in any preventive healthcare or long term condition management role were eligible. Data collection and analysis We used standard Cochrane methods to select and extract data and to appraise eligible studies. Main results We included 132 trials (N = 4,669,689). Studies spanned across several clinical areas, assessing many comparisons based on evaluation of different ATCS types and variable comparison groups. Forty-one studies evaluated ATCS for delivering preventive healthcare, 84 for managing long-term conditions, and seven studies for appointment reminders. We downgraded our certainty in the evidence primarily because of the risk of bias for many outcomes. We judged the risk of bias arising from allocation processes to be low for just over half the studies and unclear for the remainder. We considered most studies to be at unclear risk of performance or detection bias due to blinding, while only 16% of studies were at low risk. We generally judged the risk of bias due to missing data and selective outcome reporting to be unclear. For preventive healthcare, ATCS (ATCS Plus, IVR, unidirectional) probably increase immunisation uptake in children (risk ratio (RR) 1.25, 95% confidence interval (CI) 1.18 to 1.32; 5 studies, N = 10,454; moderate certainty) and to a lesser extent in adolescents (RR 1.06, 95% CI 1.02 to 1.11; 2 studies, N = 5725; moderate certainty). The effects of ATCS in adults are unclear (RR 2.18, 95% CI 0.53 to 9.02; 2 studies, N = 1743; very low certainty). For screening, multimodal ATCS increase uptake of screening for breast cancer (RR 2.17, 95% CI 1.55 to 3.04; 2 studies, N = 462; high certainty) and colorectal cancer (CRC) (RR 2.19, 95% CI 1.88 to 2.55; 3 studies, N = 1013; high certainty) versus usual care. It may also increase osteoporosis screening. ATCS Plus interventions probably slightly increase cervical cancer screening (moderate certainty), but effects on osteoporosis screening are uncertain. IVR systems probably increase CRC screening at 6 months (RR 1.36, 95% CI 1.25 to 1.48; 2 studies, N = 16,915; moderate certainty) but not at 9 to 12 months, with probably little or no effect of IVR (RR 1.05, 95% CI 0.99, 1.11; 2 studies, 2599 participants; moderate certainty) or unidirectional ATCS on breast cancer screening. Appointment reminders delivered through IVR or unidirectional ATCS may improve attendance rates compared with no calls (low certainty). For long-term management, medication or laboratory test adherence provided the most general evidence across conditions (25 studies, data not combined). Multimodal ATCS versus usual care showed conflicting effects (positive and uncertain) on medication adherence. ATCS Plus probably slightly (versus control; moderate certainty) or probably (versus usual care; moderate certainty) improves medication adherence but may have little effect on adherence to tests (versus control). IVR probably slightly improves medication adherence versus control (moderate certainty). Compared with usual care, IVR probably improves test adherence and slightly increases medication adherence up to six months but has little or no effect at longer time points (moderate certainty). Unidirectional ATCS, compared with control, may have little effect or slightly improve medication adherence (low certainty). The evidence suggested little or no consistent effect of any ATCS type on clinical outcomes (blood pressure control, blood lipids, asthma control, therapeutic coverage) related to adherence, but only a small number of studies contributed clinical outcome data. The above results focus on areas with the most general findings across conditions. In condition-specific areas, the effects of ATCS varied, including by the type of ATCS intervention in use. Multimodal ATCS probably decrease both cancer pain and chronic pain as well as depression (moderate certainty), but other ATCS types were less effective. Depending on the type of intervention, ATCS may have small effects on outcomes for physical activity, weight management, alcohol consumption, and diabetes mellitus. ATCS have little or no effect on outcomes related to heart failure, hypertension, mental health or smoking cessation, and there is insufficient evidence to determine their effects for preventing alcohol/ substance misuse or managing illicit drug addiction, asthma, chronic obstructive pulmonary disease, HIV/AIDS, hypercholesterolaemia, obstructive sleep apnoea, spinal cord dysfunction or psychological stress in carers. Only four trials (3%) reported adverse events, and it was unclear whether these were related to the intervention

    Low-Resource Unsupervised NMT:Diagnosing the Problem and Providing a Linguistically Motivated Solution

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    Unsupervised Machine Translation hasbeen advancing our ability to translatewithout parallel data, but state-of-the-artmethods assume an abundance of mono-lingual data. This paper investigates thescenario where monolingual data is lim-ited as well, finding that current unsuper-vised methods suffer in performance un-der this stricter setting. We find that theperformance loss originates from the poorquality of the pretrained monolingual em-beddings, and we propose using linguis-tic information in the embedding train-ing scheme. To support this, we look attwo linguistic features that may help im-prove alignment quality: dependency in-formation and sub-word information. Us-ing dependency-based embeddings resultsin a complementary word representationwhich offers a boost in performance ofaround 1.5 BLEU points compared to stan-dardWORD2VECwhen monolingual datais limited to 1 million sentences per lan-guage. We also find that the inclusion ofsub-word information is crucial to improv-ing the quality of the embedding
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