1,720,955 research outputs found
Learning to detect fake online reviews using readability tests and text analytics
No full textA customer highly relies on reviews when buying any product online, hence playing a crucial part in the customer's decision-making process. With the rise of online communities and portals, millions of reviews are getting posted and determining the credibility of them with such a high volume data is difficult. Although it is essential to classify them, as it profoundly impacts the business. Due to its hidden nature, fake reviews are used by companies to increase their market strength, which is a matter of concern. Many studies have been conducted with respect to this domain, where different statistical and textual analysis was performed to identify fake and genuine reviews. In this research, we propose the use of readability tests as features in combination with other general ratings and textual features on restaurant reviews datasets from Yelp for online spam review detection. We use supervised machine learning techniques such as Naïve Bayes, XGBoost, AdaBoost, and Gradient Boosting Machine for the classification of reviews using the mentioned feature sets. The results by the models are promising and displays the effectiveness of the proposed models in detecting fake reviews
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Quantitative Models for Workforce Management in a Large Service Operation
No full textPart 3: Inclusive Work Systems Design: Applying Technology to Accommodate Individual Worker’s NeedsInternational audienceThis paper develops quantitative models for optimizing employee scheduling in large labor-intense service operations that face complexities such high employee turnover, contractual service-level agreements (SLA), non-billable overtime cost, and rising minimum wages. The workforce analytics part of the model uses payroll data to characterize employee features such as consistency, overtime affinity, and retention. The business analytics part of the model ensures that adequate employees are assigned to a shift to comply with SLA while minimizing anticipated overtime cost based on the prevailing overtime salary. A Mixed Integer-Linear Program is formulated with the objective of balancing total overtime cost reduction, employee preferences, and employee features. Additionally, employees can be clustered to identify distinct patterns based on their features of consistency, overtime, and retention. The proposed approach has been applied at a North American service provider with over 4,000 employees across more than 100 sites. K-means clustering based on employee features identified four distinct clusters. Deeper analytics using mixed-effects analysis can show the contribution to profitability from reliable employees, which are limited in availability. Boosted tree importance scoring can establish the influence of moderately reliable employees on overtime cost. Furthermore, decision tree model highlighted that tactical hiring and scheduling must account for collective workforce variability rather than individual attributes in isolation. A partial dependence plot helps visualize the relationship between employee reliability and overtime, thereby helping to characterize the impact of workforce mix on cost. Key impact from this work is that the company management is working to improve its recruitment, retention, and scheduling policies to better align business needs and human capital
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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