Exploiting social media for fake reviews

We provide an overview of our recent work that studies the market for fake product reviews on Amazon.com where reviews are purchased in large private internet groups on Facebook and other sites. We find that a wide array of products purchase fake reviews, including products with many reviews and high average ratings. Buying fake reviews on Facebook is associated with a significant but short-term increase in average rating and number of reviews. We exploit a sharp but temporary policy shift by Amazon to show that rating manipulation has a large causal effect on sales. Finally, we examine whether rating manipulation harms consumers or whether it is mostly used by high-quality or young products in a manner akin to advertising. We find that after firms stop buying fake reviews, their average ratings fall and the share of one-star reviews increases significantly, particularly for young products, indicating rating manipulation is mostly used by low-quality products and is deceiving and harming consumers.

Movie Recommendation Model from Data through Online Streaming

With the Pandemic era and easy availability of internet, potential of digital movie and tv series industry is in huge demand. Hence it has led to developing an automatic movie recommendation engine and has become a popular issue. Some of these problems can be solved or at least be minimized if we take the right decisions on what kind of movies to ignore, what movies to consider. This paper examines the recommendations that are obtained with considering the sample movies that have never got an above-average rating, where average rating is defined here as the mid-value between 0 and maximum rating used, for example, 2.5 in 1 to 5 rating scale. The technique used is “collaborative filtering”. Comparison of different pre-training model, it is tried to maximize the effectiveness of semantic understanding and make the recommendation be able to reflect meticulous perception on the relationship between user utilisation and user preference. Keywords: movie recommendation system, user similarity, user similarity, consumption pattern

Investigate the Influence of Online Ratings and Reviews in Purchase Behavior Using Customer Choice Sets

The exponentially growing online reviews have become a great wealth of information into which many researchers have started tapping. Using online reviews as a source of customer feedback, product designers are able to better understand customers’ preferences and improve product design accordingly. However, while predicting future product demand as a function of product attributes and customer heterogeneity has proved to be effective, not many literatures have studied the impact of non-product-related features, such as number of reviews and average ratings, on product demand using a large-scale dataset. As such, this paper proposes a data-driven methodology to investigate the influence of online ratings and reviews in purchase behavior by using discrete choice analysis. In the absence of information about the true customer choice set, we generate an estimated customer choice set based on a probability sampling using customer clustering and product clustering. In order to examine the effect of number of reviews and average rating, we have computed, for all the laptops in the choice set of each customer, the number of reviews and thus average rating at the date of this particular customer’s review. Using laptops for our case study, our experiment has shown that the number of reviews and average ratings are statistically significant, and the inclusion of these features will greatly improve the predictive ability of the model.

FORECASTING THE RESULTS OF THE SINGLE ENTRANCE EXAM IN A FOREIGN LANGUAGE BY BACHELORS OF THE INSTITUTION OF HIGHER EDUCATION

The paper provides information on the need to pass the “Unified entrance exam” in a foreign (English) language by students who have received a bachelor’s degree and wish to continue their studies to obtain a master’s degree. It is determined that when working with undergraduate students, it is advisable, firstly, to determine the percentage of graduates whose passing EVE is unlikely, and secondly, to intensify work with such graduates to increase this probability. The task was set to create a model for predicting the results of the unified entrance exam in a foreign language by bachelor’s graduates of higher education institutions upon entering the master’s program. A number of factors that affect the EVE score are proposed, namely: competitive score at enrollment (indicator of the student’s basic level), rating (assessment) based on the results of the first year of study (exam in the compulsory subject “Foreign Language”), choice “Foreign language” in the 2-3rd year (maximum of all or “0”, if the student did not choose), the rating of additional classes “Foreign language” in the 4th year, the average rating for the penultimate session (indicator “current” student’s attitude to the educational process), the fact of having additional points (an indicator of the student’s interest in other activities than learning), the average rating of a bachelor’s degree (an indicator of the general student’s attitude to the educational process). The available data concerning students of two years of the department of intelligent decision-making systems of the Donbas State Engineering Academy are given. A method of artificial neural networks with a two-layer perceptron architecture with ten neurons in each hidden layer, a sigmoid activation function, and an error backpropagation algorithm for network training is proposed. Calculations were performed in the Deductor Studio Lite environment, their results were analyzed. It is noted that the proposed approach to forecasting can be applied when working with undergraduate students, to determine the percentage of graduates whose EVI is unlikely to pass, and to intensify work with such graduates to increase this probability. Keywords: educational and qualification level, the only entrance exam, forecasting, artificial neural network, perceptron, sigmoid, network training.

On the Effect of Standing and Seated Viewing of 360∘ Videos on Subjective Quality Assessment: A Pilot Study

Due to the advances in head-mounted displays (HMDs), hardware and software technologies, and mobile connectivity, virtual reality (VR) applications such as viewing 360∘ videos on HMDs have seen an increased interest in a wide range of consumer and vertical markets. Quality assessment of digital media systems and services related to immersive visual stimuli has been one of the challenging problems of multimedia signal processing. Specifically, subjective quality assessment of 360∘ videos presented on HMDs is needed to obtain a ground truth on the visual quality as perceived by humans. Standardized test methodologies to assess the subjective quality of 360∘ videos on HMDs are currently not as developed as for conventional videos and are subject to further study. In addition, subjective tests related to quality assessment of 360∘ videos are commonly conducted with participants seated on a chair but neglect other options of consumption such as standing viewing. In this paper, we compare the effect that standing and seated viewing of 360∘ videos on an HMD has on subjective quality assessment. A pilot study was conducted to obtain psychophysical and psychophysiological data that covers explicit and implicit responses of the participants to the shown 360∘ video stimuli with different quality levels. The statistical analysis of the data gathered in the pilot study is reported in terms of average rating times, mean opinion scores, standard deviation of opinion scores, head movements, pupil diameter, galvanic skin response (GSR), and simulator sickness scores. The results indicate that the average rating times consumed for 360∘ video quality assessment are similar for standing and seated viewing. Further, the participants showed higher resolving power among different 360∘ video quality levels and were more confident about the given opinion scores for seated viewing. On the other hand, a larger scene exploration of 360∘ videos was observed for standing viewing which appears to distract from the quality assessment task. A slightly higher pupil dilation was recorded for standing viewing which suggests a slightly more immersed experience compared to seated viewing. GSR data indicate a lower degree of emotional arousal in seated viewing which seems to allow the participants to better conduct the quality assessment task. Similarly, simulator sickness symptoms are kept significantly lower when seated. The pilot study also contributes to a holistic view of subjective quality assessment and provides indicative ground truth that can guide the design of large-scale subjective tests.

Restaurant Recommendation System using Machine Learning

Nowadays a big challenge when going out to a new restaurant or cafe, people usually use websites or applications to look up nearby places and then choose one based on an average rating. But most of the time the average rating isn't enough to predict the quality or hygiene of the restaurant. Different people have different perspectives and priorities when evaluating a restaurant. Many online businesses now have implemented personalized recommendation systems which basically try to identify user preferences and then provide relevant products to enhance the users experience . In turn, users will be able to enjoy exploring what they might like with convenience and ease because of the recommendation results. Finding an ideal restaurant can be a struggle because the mainstream recommender apps have not yet adopted the personalized recommender approach. So we took up this challenge and we aim to build the prototype of a personalized recommender system that incorporates metadata which is basically the information provided by interactions of customers and restaurants online(reviews), which gives a pretty good idea of customers satisfaction and taste as well as features of the restaurant. This type of approach enhances user experience of finding a restaurant that suits their taste better. This paper has used a package called lightfm(the library of python for implementing popular recommendation algorithms) and the dataset from yelp. There are different methods of filtering the data, here we have used Hybrid filtering which is a combination of Content-based filtering (CBF) and Collaborative Filtering (CF). Since the results from Hybrid filtering are far more closer to accuracy than CBF or CF respectively. Then hybrid filtering gives results in the form of personalized recommendations for users after training and testing of the data

Analysis of the spelling, effective sentences, and paragraphs in the students scientific papers

This study aims to determine the level of use of spelling, effective sentences, and Indonesian language paragraphs in scientific papers applied by undergraduate students of the State Polytechnic of Bali in the form of theses. This research is important because there is a tendency to use spelling, effective sentences, and paragraphs in student scientific papers that are not in accordance with applicable rules such as prepositions, punctuation. The method used in this study is a qualitative method, while the method of data collection in the form of documentation with qualitative descriptive analysis. Studies on spelling order, each of them scored: Managerial Accounting Study Program 98.73, International Business Study Program 98.96, Tourism Business Management Study Program 99.02, Construction Management Study Program 98.51 with an average rating of 98.80. At the sentence level each gets a value: Managerial Accounting Study Program 83.72, International Business Study Program 85.22, Tourism Business Management Study Program 77.25, and Construction Management Study Program 74.75, while at the paragraph level each value: Accounting Study Program Managerial 70.74, International Business Study Program 61.20, Tourism Business Management Study Program 60.31, and Construction Management Study Program 66.87, with an average rating of 64.78. Thus, it can be concluded that spelling ability, effective sentence, and student paragraphs applied bachelor of Polytechnic Bali is very good.

PENGEMBANGAN MEDIA PEMBELAJARAN E-LEARNING MENGGUNAKAN MOODLE BERBASIS E-MODUL PADA PEMBELAJARAN INTALASI PENERANGAN LISTRIK UNTUK KELAS XI TITL SMK SWASTA IMELDA MEDAN

This study aims to know the feasibility of media, as well as to know the response to the development of e-learning media using moodle-based e-modules on the learning of electrical lighting installations at SMKS Imelda Medan. This e-learning development uses addie development model adapted from Mollenda and Reiser (2003). namely: (1) analysis, (2) design, (3) development, (4) implementation, and (5) evaluation. E-learning feasibility assessment is conducted by material experts, media experts, and teachers as respondents. Data collection techniques used are questionnaire techniques to obtain quantitative data as primary data and qualitative data in the form of suggestions or comments as data for e-learning improvements. Quantitative data obtained is then converted into qualitative data using ideal assessment criteria. The results showed that: e-learning has "feasible" criteria from material experts with an average assessment of 4.00, from e-learning media experts have "feasible" criteria with an average rating of 4.13; e-learning trial results to respondents showed that e-learning has a "high acceptance" criteria with an average rating of 4.05. Based on the results of the development research obtained, it can be concluded that the development of e-learning using moodle-based e-modules in SMKS Imelda Medan is feasible to be developed. Key Words: E-Learning Moodle, learning media, E-module AbstrakPenelitian ini bertujuan untuk mengetahui kelayakan media, serta mengetahui respon terhadap pengembangan media e-learning menggunakan moodle berbasis e-modul pada pembelajaran instalasi penerangan listrik di SMKS Imelda Medan. Pengembangan e-learning ini menggunakan model pengembangan ADDIE diadaptasi dari Mollenda dan Reiser (2003). yakni: (1) analisis, (2) desain, (3) pengembangan, (4) implementasi, dan (5) evaluasi. Penilaian kelayakan e-learning dilakukan oleh ahli materi, ahli media, dan guru sebagai responden. Teknik pengumpulan data yang digunakan adalah teknik angket untuk memperoleh data kuantitatif sebagai data primer dan data kualitatif berupa saran atau komentar sebagai data untuk perbaikan e-learning. Data kuantitatif yang diperoleh kemudian dikonversi menjadi data kualitatif menggunakan kriteria penilaian ideal. Hasil penelitian menunjukkan bahwa: e-learning memiliki kriteria “layak” dari ahli materi dengan rerata penilaian 4.00, dari ahli media e-learning memiliki kriteria “layak” dengan rerata penilaian 4.13; hasil uji coba e-learning kepada responden menunjukkan bahwa e-learning memiliki kriteria “akseptansi tinggi” dengan rerata penilaian 4.05. Berdasarkan hasil dari penelitian pengembangan yang diperoleh maka dapat disimpulkan bahwa pengembangan e-learning menggunakan moodle berbasis e-modul di SMKS Imelda Medan layak untuk dikembangkan. Kata Kunci: E-Learning Moodle, Media Pembelajaran, E-Modul

Evaluation of Patient Preference and Perception Regarding the Clinical Use of Autologous Versus Allogeneic Cell Therapy in Orthopedic Surgery

Background: Cell therapy has become a hot topic in orthopedics, with significant research dedicated to improving physicians’ understanding of its efficacy. However, little is known about patients’ cell therapy knowledge. Questions/Purposes: The aims of this study were to (1) evaluate patients’ perceptions of cell therapy in orthopedics, (2) determine whether patients have a preference for autologous or allogeneic cell therapy, and (3) assess patient concerns about cell therapy. Methods: Consecutive outpatients of an orthopedic clinic were surveyed from June 2019 to January 2020. All patients were 18 years old or older and being seen for an orthopedic intervention, including rotator cuff repair, anterior cruciate ligament (ACL) reconstruction, arthroscopic meniscectomy, or a cartilage repair procedure such as an osteochondral allograft transplantation or matrix-associated autologous chondrocyte implantation. Results: A total of 50 patients were surveyed (mean age: 53 years). The patients’ average rating for likelihood to use autologous cells was 8.86 ± 2.2 out of 10 and the average rating for likelihood to use allogeneic cells was 6.24 ± 3.3; 46% of patients had no specific concerns about autologous cell therapy, while 28% expressed concerns about efficacy, and 12% had concerns about donor age. The top 2 “main concerns” about allogeneic cell therapy were disease transmission (30%) and immune reaction (24%). Conclusions: This survey found that patients asserted a preference for autologous cell therapy in orthopedics. Further research is necessary to further elucidate the factors related to cell therapy that are most important to patients.

The Effect of Price on Firm Reputation

Although a business’s reputation can affect its pricing, prices can also affect its reputation. To explore the effect of prices on reputation, we investigate daily data on menu prices and online ratings from a large rating and ordering platform. We find that a price increase of 1% leads to a decrease of 3%–5% in the average rating. Consistent with this, the overall distribution of ratings for cheaper restaurants is similar to that of more expensive restaurants. Finally, these effects do not seem to be driven by consumer retaliation against price changes but by changes in absolute price levels. This paper was accepted by Duncan Simester, marketing.