20 research outputs found

    Are Online Consumer Reviews Credible? A Predictive Model based on Deep Learning

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    As the importance of online consumer reviews has grown, the concerns about their credibility being damaged by the presence of fake reviews have also grown. Extant literature reveals the importance of online reviews for consumers. Yet, there is a lack of research in the literature that considers consumer perception while developing a predictive model for the credibility of online reviews. This research aims to fill this gap by combining two different streams in the literature namely human-driven and data-driven approaches. To do so, we use two datasets with different labelling approaches to develop a predictive model, the first one is labelled based on the Yelp filtering algorithm and the second one is labelled based on the crowd’s perception towards credibility. Results from our predictive model reveal that it can predict credibility with a performance of 82% AUC, using reviews’ attributes namely, length, subjectivity, readability, extremity, external and internal consistency

    What Makes a Review Credible? Heuristic and Systematic Factors for the Credibility of Online Reviews

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    In the digital transformation era, online reviews have become an important source of information for decisions about purchases. Research shows that online reviews influence users’ behaviors and product sales. However, questions remain about how and why users assess the credibility of online reviews for different products/services on different websites. Using semi-structured interviews as a way of understanding how users assess the credibility of online reviews, we propose a comprehensive credibility analysis model for online reviews. The proposed model extends a model we previously proposed; and uses the Heuristic Systematic Model (HSM) as a theoretical lens, which helps us to understand different features that impact the credibility of online reviews. Our findings reveal several factors which impact the credibility of online reviews that have not been identified in the previous literature

    A newly emerged cutaneous leishmaniasis focus in central Iran

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    SummaryObjectivesThis study was performed to evaluate the epidemiological status of cutaneous leishmaniasis (CL) in the most important endemic foci of Qom Province, central Iran. The city of Qom is the largest center for Shi’a scholarship in the world and is a significant pilgrimage destination.MethodsDuring 2006–2011, all suspected CL patients with skin lesion(s) referred to regional health centers of Ghomrood and Ghanavat regions, and all actively detected cases, were examined clinically and parasitologically for CL. Patient information was recorded and patients were categorized based on the number and size of the lesions. Odds ratios (OR) of different risk factors were calculated.ResultsA total of 849 (59.2% male, 40.8% female) confirmed cases of CL were enrolled; the average incidence rate of the disease was 14.9 per 100000 people. During the study period 2006–2011, the trend in CL incidence showed no sudden variations in the areas studied, except for an outbreak of CL in 2009. Leishmania major was identified as the causative agent based on internal transcribed spacer 1 (ITS1) ribosomal DNA PCR analysis. During the study period, the age distribution of CL cases was relatively stable, with the majority (50%) of patients aged 1–25 years. Most cases (n = 468; 55.1%) had a single lesion and 82 (9.6%) patients had four or more lesions (range 1–29). The risk of developing multiple lesions was significantly increased in patients with seasonal jobs (summer workers) (p = 0.023; OR 1.516) and significantly decreased in patients who were affected in winter (p = 0.010; OR 0.398). The risk of developing large-sized lesions (>1cm) was significantly increased in patients in the age groups >25 years (p = 0.001–0.015; OR 2.5–3.5) and decreased in patients with seasonal jobs (summer workers) (p = 0.005; OR 0.570).ConclusionsThe present data show the importance of CL as a health problem in suburban areas of Qom Province. In order to identify other epidemiological aspects of leishmaniasis in this area, studies on vectors and reservoirs are recommended. Since leishmaniasis caused by L. major is typically zoonotic, control measures should focus on rodents as the main reservoirs and Phlebotomus papatasi as the main vector. Awareness should be raised in the high-risk populations comprising people with diabetes, young adults (<25 years old), and those who work outdoors during the summer

    Scorpion fauna and epidemiological aspects of scorpionism in southeastern Iran

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    ABSTRACTObjectiveTo identify the scorpion fauna and classify the epidemiological aspects of scorpionism in an endemic region, Southeast Iran.MethodsScorpionism data were collected from health centers and hospitals in Sistan-Baluchestan Province during 2010-2011. Specimens were collected at night, using UV light, between May and October 2012.ResultsIn total, 246 scorpions were collected from two families (Buthidae and Scorpionidae). Five species including Odontobuthus odonturus, Hottentotta (Buthotus) jayakari, Compsobuthus matthiesseni, Scorpio maurus and Orthochirus scrobiculosus are reported for the first time from this area. Androctonus crassicauda was the dominant species. In total, 3 638 scorpion sting cases were recorded by health system, the majority of which were females. Stings mostly occurred in July and the age group of 15–24 years presented the highest frequency. Scorpionism decreased during 2011 compared with that in 2010 (68.2%).ConclusionsBased on the results, scorpionism is a serious health problem in this area and increasing knowledge of residents regarding the prevention methods of scorpion stings is recommended. Additional research on the scorpion fauna, their ecological and molecular variety in this part of the country is needed as well as the correlation between scorpions' species and the clinical signs and symptoms

    Who Gets the Job? Synthesis of Literature Findings on Provider Success in Crowdsourcing Marketplaces

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    Background: Over the past decade, crowdsourcing marketplaces — online exchange platforms which facilitate commercial outsourcing of services — have witnessed a dramatic growth in the number of participants (service providers and customers) and the value of outsourced services. Deciding about the most appropriate provider is a key challenge for customers in crowdsourcing marketplaces because available information about providers may be incomplete and sometimes irrelevant for customer decisions. Ineffective information impedes many service providers to develop long-term relationships with customers, obtain projects on a regular basis and survive on crowdsourcing marketplaces. Previous studies have investigated the impact of a range of factors on customers’ choice decisions and providers’ success, given the important role of customer–provider relationship development for long-term success on crowdsourcing marketplaces. Method: This paper reviews the literature of crowdsourcing marketplaces with the aim of developing a comprehensive list of factors that influence customers’ choice decisions and providers’ success. Results: We found 31 conceptually distinct profile information components/factors that determine customers’ choices and providers’ business outcomes on crowdsourcing marketplaces. Conclusion: We classified these 31 factors into five major categories: 1) prior relationship between a customer and a provider or a customer’s invitation, 2) providers’ bidding behavior, 3) crowdsourcing marketplace or auction characteristics, 4) providers’ profile information, and 5) customer characteristics. The main factors in each category, associated considerations, related literature gaps and avenues for future research are discussed in detail

    In the Importance of EFL Learners' Writing Skill: Is there any Relation between Writing Skill and Content Score of English Essay Test?

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    Achievement test scores are used to diagnose strengths, weaknesses, and a basis for awarding prizes, scholarship, or degrees. They are also used in evaluating the influences of course of study, teachers, teaching methods, and other factors considered to be significant in educational practice. Still, sometimes there is a gap in the score of essay tests and the existing knowledge of examinees. In the present study, the relationship between writing skill and the academic achievement of Iranian EFL students was examined to find a logical connection between them. The results of four final exams as content scores were examined and scored again in term of writing ability in analytical scoring scheme according to IELTS criteria. Then the average of two sets of scores calculated by two raters was compared with content scores of the same tests. The results showed that correlation between content score of all students and their writing skills is meaningful at 0.01 level of significance. The results showed that there is a strong relationship between EFL students' degree of content score and their writing skill

    Investigating gender and racial biases in DALL-E Mini Images

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    Generative artificial intelligence systems based on transformers, including both text-generators like GPT-3 and image generators like DALL-E 2, have recently entered the popular consciousness. These tools, while impressive, are liable to reproduce, exacerbate, and reinforce extant human social biases, such as gender and racial biases. In this paper, we systematically review the extent to which DALL-E Mini suffers from this problem. In line with the Model Card published alongside DALL-E Mini by its creators, we find that the images it produces tend to represent dozens of different occupations as populated either solely by men (e.g., pilot, builder, plumber) or solely by women (e.g., hairdresser, receptionist, dietitian). In addition, the images DALL-E Mini produces tend to represent most occupations as populated primarily or solely by White people (e.g., farmer, painter, prison officer, software engineer) and very few by non-White people (e.g., pastor, rapper). These findings suggest that exciting new AI technologies should be critically scrutinized and perhaps regulated before they are unleashed on society
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