Search results for: overview of reviews

Authors: Sarif Ullah Patwary, Matthew Heinrich, Brandon Payne

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The ubiquity of web 2.0 platforms, in the form of wikis, social media (e.g., Facebook, Twitter, etc.) and online review portals (e.g., Yelp), helps shape today’s apparel consumers’ purchasing decision. Online reviews play important role towards consumers’ apparel purchase decision. Each of the consumer reviews carries a sentiment (positive, negative or neutral) towards products. Commercially, apparel brands and retailers analyze sentiment of this massive amount of consumer review data to update their inventory and bring new products in the market. The purpose of this study is to analyze consumer reviews of selected apparel stores with a view to understand, 1) the difference of sentiment expressed through men’s and woman’s text reviews, 2) the difference of sentiment expressed through men’s and woman’s star-based reviews, and 3) the difference of sentiment between star-based reviews and text-based reviews. A total of 9,363 reviews (1,713 men and 7,650 women) were collected using Yelp Dataset Challenge. Sentiment analysis of collected reviews was carried out in two dimensions: star-based reviews and text-based reviews. Sentiment towards apparel stores expressed through star-based reviews was deemed: 1) positive for 3 or 4 stars 2) negative for 1 or 2 stars and 3) neutral for 3 stars. Sentiment analysis of text-based reviews was carried out using Bing Liu dictionary. The analysis was conducted in IPyhton 5.0. Space. The sentiment analysis results revealed the percentage of positive text reviews by men (80%) and women (80%) were identical. Women reviewers (12%) provided more neutral (e.g., 3 out of 5 stars) star reviews than men (6%). Star-based reviews were more negative than the text-based reviews. In other words, while 80% men and women wrote positive reviews for the stores, less than 70% ended up giving 4 or 5 stars in those reviews. One of the key takeaways of the study is that star reviews provide slightly negative sentiment of the consumer reviews. Therefore, in order to understand sentiment towards apparel products, one might need to combine both star and text aspects of consumer reviews. This study used a specific dataset consisting of selected apparel stores from particular geographical locations (the information was not given for privacy concern). Future studies need to include more data from more stores and locations to generalize the findings of the study.

Keywords: apparel, consumer review, sentiment analysis, gender

Procedia PDF Downloads 144

Authors: Yu Hung Chiang, Hei Chia Wang

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Nowadays, tourism has become a part of life. Before reserving hotels, customers need some information, which the most important source is online reviews, about hotels to help them make decisions. Due to the dramatic growing of online reviews, it is impossible for tourists to read all reviews manually. Therefore, designing an automatic review analysis system, which summarizes reviews, is necessary for them. The main purpose of the system is to understand the opinion of reviews, which may be positive or negative. In other words, the system would analyze whether the customers who visited the hotel like it or not. Using sentiment analysis methods will help the system achieve the purpose. In sentiment analysis methods, the targets of opinion (here they are called the feature) should be recognized to clarify the polarity of the opinion because polarity of the opinion may be ambiguous. Hence, the study proposes an unsupervised method using Part-Of-Speech pattern and multi-lexicons sentiment analysis to summarize all reviews. We expect this method can help customers search what they want information as well as make decisions efficiently.

Keywords: text mining, sentiment analysis, product feature extraction, multi-lexicons

Procedia PDF Downloads 311

Authors: Jenna Barriault, Reeshma Haji

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Online consumer behaviourand reliance on online reviews may be more pervasive than ever, andthis necessitates a better scientific understanding of the widespread phenomenon of online deception. The present research focuses on the understudied topic of deceiver’s distrust, where those who engage in deception later have less trust in others in the context of online restaurant reviews. The purpose was to examine deception and valence in online restaurant reviews and the effects they had on deceiver’s distrust. Undergraduate university students (N = 76) completed an online study where valence was uniquely manipulated by telling participants that either positive (or negative reviews) were influential and asking them to write a correspondingly valenced review. Deception was manipulated in the same task. Participants in the deception condition were asked to write an online restaurant review that was counter to their actual experience of the restaurant (negative review of a restaurant they liked, positive review of the restaurant they did not like). In the no deception condition, participants were asked to write a review that they actually liked or didn’t like (based on the valence condition to which they were randomly assigned). Participants’ trust was then assessed through various measures, includingfuture reliance on online reviews. There was a main effect of deception on reliance on online reviews. Consistent with deceiver’s distrust, those who deceived reported that they would rely less on online reviews. This study demonstrates that even when participants are induced to write a deceptive review, it can result in deceiver’s distrust, thereby lowering their trust in online reviews. If trust or reliance can be altered through deception in online reviews, people may start questioning the objectivity or true representation of a company based on such reviews. A primary implication is that people may reduce theirreliance upon online reviews if they know they are easily subject to manipulation. The findings of this study also contribute to the limited research regarding deceiver’s distrust in an online context, and further research is clarifying the specific conditions in which it is most likely to occur.

Keywords: deceiver’s distrust, deception, online reviews, trust, valence

Procedia PDF Downloads 101

Authors: Subhadeep Mandal, Sujoy Bhattacharya, Pabitra Mitra, Diya Guha Roy, Seema Bhattacharya

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E-commerce firms allow customers to evaluate and review the things they buy as a positive or bad experience. The e-commerce transaction processes are made up of a variety of diverse organizations and activities that operate independently but are connected together to complete the transaction (from placing an order to the goods reaching the client). After a negative shopping experience, clients frequently disregard the critical assessment of these businesses and submit their feedback on an all-over basis, which benefits certain enterprises but is tedious for others. In this article, we solely dealt with negative reviews and attempted to distinguish between negative reviews where the e-commerce firm is explicitly blamed by customers for a bad purchasing experience and other negative reviews.

Keywords: e-commerce, online shopping, customer reviews, customer behaviour, text analytics, n-grams classification

Procedia PDF Downloads 237

Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad

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As a result of the growth of the web, people are able to express their views and opinions. They can now post reviews of products at merchant sites and express their views on almost anything in internet forums, discussion groups, and blogs. Therefore, the number of product reviews has grown rapidly. The large numbers of reviews make it difficult for manufacturers or businesses to automatically classify them into different semantic orientations (positive, negative, and neutral). For sentiment classification, most existing methods utilize a list of opinion words whereas this paper proposes a fuzzy approach for evaluating sentiments expressed in customer product reviews, to predict the strength levels (e.g. very weak, weak, moderate, strong and very strong) of customer product reviews by combinations of adjective, adverb and verb. The proposed fuzzy approach has been tested on eight benchmark datasets and obtained 74% accuracy, which leads to help the organization with a more clear understanding of customer's behavior in support of business planning process.

Keywords: fuzzy logic, customer product review, sentiment analysis

Procedia PDF Downloads 342

Authors: Atefeh Heydari, Mohammadali Tavakoli, Naomie Salim

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In recent years, we have witnessed that online reviews are the most important source of customers’ opinion. They are progressively more used by individuals and organisations to make purchase and business decisions. Unfortunately, for the reason of profit or fame, frauds produce deceptive reviews to hoodwink potential customers. Their activities mislead not only potential customers to make appropriate purchasing decisions and organisations to reshape their business, but also opinion mining techniques by preventing them from reaching accurate results. Spam reviews could be divided into two main groups, i.e. multiple and singleton spam reviews. Detecting a singleton spam review that is the only review written by a user ID is extremely challenging due to lack of clue for detection purposes. Singleton spam reviews are very harmful and various features and proofs used in multiple spam reviews detection are not applicable in this case. Current research aims to propose a novel supervised technique to detect singleton spam reviews. To achieve this, various features are proposed in this study and are to be combined with the most appropriate features extracted from literature and employed in a classifier. In order to compare the performance of different classifiers, SVM and naive Bayes classification algorithms were used for model building. The results revealed that SVM was more accurate than naive Bayes and our proposed technique is capable to detect singleton spam reviews effectively.

Keywords: classification algorithms, Naïve Bayes, opinion review spam detection, singleton review spam detection, support vector machine

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Authors: Paula Simões, Isabel Natário

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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.

Keywords: spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data

Procedia PDF Downloads 570

Authors: Jimmylen Tonio, Ali Anudin, Rochelle Irene G. Lucas

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Alongside the progress of electronic-business websites, consumers have become more comfortable with online shopping. It has become customary for consumers that prior to purchasing a product or availing services, they consult online reviews info as bases in evaluating and deciding whether or not they should push thru with their procurement of the product or service. Subsequently, after purchasing, consumers tend to post their own comments of the product in the same e-business websites. Because of this, product reviews (PRS) have become an indispensable feature in online businesses equally beneficial for both business owners and consumers. This study explored the linguistic features and motivations of online product reviews on selected Philippine online shops, LAZADA and SHOPEE. Specifically, it looked into the lexical features of the PRs, the factors that motivated consumers to write the product reviews, and the difference of lexical preferences between male and female when they write the reviews. The findings revealed the following: 1. Formality of words in online product reviews primarily involves non-standard spelling, followed by abbreviated word forms, colloquial contractions and use of coined/novel words; 2. Paralinguistic features in online product reviews are dominated by the use of emoticons, capital letters and punctuations followed by the use of pictures/photos and lastly, by paralinguistic expressions; 3. The factors that motivate consumers to write product reviews varied. Online product reviewers are predominantly driven by venting negative feelings motivation, followed by helping the company, helping other consumers, positive self-enhancement, advice seeking and lastly, by social benefits; and 4. Gender affects the word frequencies of product online reviews, while negation words, personal pronouns, the formality of words, and paralinguistic features utilized by both male and female online product reviewers are not different.

Keywords: lexical choices, motivation, online shop, product reviews

Procedia PDF Downloads 132

Authors: Zhi Liu, Xian Peng, Monika Domanska, Lingyun Kang, Sannyuya Liu

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Massive Open education has become increasingly popular among worldwide learners. An increasing number of course reviews are being generated in Massive Open Online Course (MOOC) platform, which offers an interactive feedback channel for learners to express opinions and feelings in learning. These reviews typically contain subjective emotion and topic information towards the courses. However, it is time-consuming to artificially detect these opinions. In this paper, we propose an emotion-oriented topic detection model to automatically detect the students’ opinioned aspects in course reviews. The known overall emotion orientation and emotional words in each review are used to guide the joint probabilistic modeling of emotion and aspects in reviews. Through the experiment on real-life review data, it is verified that the distribution of course-emotion-aspect can be calculated to capture the most significant opinioned topics in each course unit. This proposed technique helps in conducting intelligent learning analytics for teachers to improve pedagogies and for developers to promote user experiences.

Keywords: Massive Open Online Course (MOOC), course reviews, topic model, emotion recognition, topical aspects

Procedia PDF Downloads 248

Authors: Sona Babu Rathinam, Lavanya Dharmendran, Therraddi Mutthu

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Objectives: The purpose of this paper is to provides an overview of the neuroendocrine tumors that arise in the oral cavity. Material and Methods: An overview of the relevant papers on neuroendocrine tumors of the oral cavity by various authors was studied and summarized. Results: On the basis of the relevant studies, this paper provides an overview of the classification and histological differentiation of the neuroendocrine tumors that arise in the oral cavity. Conclusions: The basis of classification of neuroendocrine tumors is largely determined by their histologic differentiation. Though they reveal biologic heterogeneity, there should be an awareness of the occurrence of such lesions in the oral cavity to enable them to be detected and treated early.

Keywords: malignant peripheral nerve sheath tumor, olfactory neuroblastoma, paraganglioma, schwannoma

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Authors: Nasrine Olson

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With over 70,000 scholarly publications on the topic of biosensors, an overview of the field has become a challenge. To facilitate, there are currently over 700 expert-reviews of publications on biosensors and related topics. This study focuses on these review papers in order to provide a Meta-Review of the area. This paper provides a statistical analysis and overview of biosensor-related review papers. Comprehensive searches are conducted in the Web of Science, and PubMed databases and the resulting empirical material are analyzed using bibliometric methods and tools. The study finds that the biosensor-related review papers can be categorized in five related subgroups, broadly denoted by (i) properties of materials and particles, (ii) analysis and indicators, (iii) diagnostics, (iv) pollutant and analytical devices, and (v) treatment/ application. For an easy and clear access to the findings visualization of clusters and networks of connections are presented. The study includes a temporal dimension and identifies the trends over the years with an emphasis on the most recent developments. This paper provides useful insights for those who wish to form a better understanding of the research trends in the area of biosensors.

Keywords: bibliometrics, biosensors, meta-review, statistical analysis, trends visualization

Procedia PDF Downloads 193

Authors: Karima Chaabna, Sohaila Cheema, Amit Abraham, Hekmat Alrouh, Ravinder Mamtani, Javaid I. Sheikh

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We aimed to assess the production of systematic reviews (SRs) that synthesize observational studies discussing population health issues in the Middle East and North Africa (MENA). Two independent reviewers systematically searched MEDLINE through PubMed. Between 2008-2016, 5,747 articles (reviews, systematic reviews, and meta-analyses) were identified. Following a multi-stage screening process, 387 SRs (with or without meta-analysis) on population health issues in the MENA were included in our overview. Citation numbers for each SR were retrieved from Google Scholar. Impact factor of the journal during the publication year for the included SRs was retrieved from the Institute of Scientific Information’s Journal Citation Report. We conducted linear regression analysis to assess time trends of number of publications according to SRs’ characteristics. We characterized a linear statistically significant increase in the annual numbers of SRs that summarize observational studies on the MENA population health (p-value<0.0001, R2=0.95), from 15 in 2008 to 81 in 2016. Our analysis reveals also linear statistically significant increases in numbers of SRs published by authors affiliated to institutions located inside MENA and/or neighboring countries (N=113, p-value < 0.0001, R²=0.90), by authors located outside MENA (N=155, p-value=0.0007, R²=0.82), and by collaborating authors affiliated to institutions located outside MENA and inside the region and/or in MENA’s neighboring countries (total number of SRs (N)= 119, p-value=0.0004, R²=0.85). Furthermore, these SRs were published in journals with an IF ranging from 0 to 47.8 (median=2.1). Linear statistically significant increases in numbers of published SRs were demonstrated in journals’ impact factor (IF) categories (IF=[0-2[: R²=0.79, p-value=0.0012; IF=[2-4[:R²=0.86, p-value=0.0003; and IF=[4-6[:R²=0.53, p-value=0.026). Additionally, annual numbers of citations to the SRs varied between 0 and 471 (median=7). While each year, a couple of SRs were getting more than 50 annual citations, there were linear statistically significant increases in numbers of published SRs with an annual number of citations at [0-10[(R²=0.89, p-value=0.00014) and at [10-50[ (R²=0.76, p-value=0.0021). Between 2008-2016, increasingly SRs that summarize observational studies on population health issues in the MENA were published. Authors of these SRs were located inside and/or outside the MENA region and an increasing number of collaborations were seen. Increasing numbers of SRs were predominantly observed in journals with an IF between zero and six. Interestingly, SRs covering MENA region countries were being increasingly cited, indicating an escalation of interest in this region’s population health issues.

Keywords: bibliometric, citation, impact factor, Middle East and North Africa, population health, systematic review

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Authors: Joris Zufferey, Roderick John Lawrence

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This paper provides an overview of the state of the art about the positive health impacts of exposure to natural outdoor environments. It presents the results of a “review of reviews” in terms of empirical evidence and identifies some key questions. Finally, the authors stress the need to develop more interdisciplinary and systemic contributions. This synthesis of empirical research has been done as part of the EU- FP7 PHENOTYPE research project.

Keywords: Exposure, environment, phenotype, salutogenic effects

Procedia PDF Downloads 377

Authors: Ibrahim Nadeem, Mohammed Rahman, Yasser Ad-Dab’Bagh, Mahmood Akhtar

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Depression is one of the most prevalent mental illnesses and is often associated with various other medical disorders. In this review, we aim to evaluate existing systematic reviews that investigate the use of probiotics as a treatment for depressive symptoms. Five online databases were searched for relevant studies up to December 2017. Systematic reviews that included randomized controlled trials assessing the efficacy of probiotics in the treatment of depressive symptoms were included. Seven systematic reviews met the inclusion criteria. Three of these reviews conducted meta-analyses, out of which, two found probiotics to significantly improve depressive symptoms in the sample population. Two meta-analyses conducted subgroup analysis based on health status, and both found probiotics to significantly decrease depressive symptoms in patients with major depressive disorder, but only one review found it to significantly decrease in healthy patients. Another subgroup analysis was conducted based on age, and found probiotics to produce significant effects on subjects under the age of 60, but close to no effect on patients over the age of 65. Out of the four reviews that conducted qualitative analysis, three reviews concluded that probiotics have the potential to be used as a treatment. Due to the differences in clinical trials, a definitive effect of probiotics on depressive symptoms cannot be concluded. Nonetheless, probiotics seem to produce a significant therapeutic effect for subjects with pre-existing depressive symptoms. Further studies are warranted for definitive conclusions.

Keywords: depression, gut-brain axis, gut microbiota, probiotic, psychobiotic

Procedia PDF Downloads 120

Authors: Veronica S. Moertini, Vinsensius Kevin, Gede Karya

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Customer reviews have been collected by many kinds of e-commerce websites selling products, services, hotel rooms, tickets and so on. Each website collects its own customer reviews. The reviews can be crawled, collected from those websites and stored as big data. Text analysis techniques can be used to analyze that data to produce summarized information, such as customer opinions. Then, these opinions can be published by independent service provider websites and used to help customers in choosing the most suitable products or services. As the opinions are analyzed from big data of reviews originated from many websites, it is expected that the results are more trusted and accurate. Indonesian customers write reviews in Indonesian language, which comes with its own structures and uniqueness. We found that most of the reviews are expressed with “daily language”, which is informal, do not follow the correct grammar, have many abbreviations and slangs or non-formal words. Hadoop is an emerging platform aimed for storing and analyzing big data in distributed systems. A Hadoop cluster consists of master and slave nodes/computers operated in a network. Hadoop comes with distributed file system (HDFS) and MapReduce framework for supporting parallel computation. However, MapReduce has weakness (i.e. inefficient) for iterative computations, specifically, the cost of reading/writing data (I/O cost) is high. Given this fact, we conclude that MapReduce function is best adapted for “one-pass” computation. In this research, we develop an efficient technique for extracting or mining opinions from big data of Indonesian reviews, which is based on MapReduce with one-pass computation. In designing the algorithm, we avoid iterative computation and instead adopt a “look up table” technique. The stages of the proposed technique are: (1) Crawling the data reviews from websites; (2) cleaning and finding root words from the raw reviews; (3) computing the frequency of the meaningful opinion words; (4) analyzing customers sentiments towards defined objects. The experiments for evaluating the performance of the technique were conducted on a Hadoop cluster with 14 slave nodes. The results show that the proposed technique (stage 2 to 4) discovers useful opinions, is capable of processing big data efficiently and scalable.

Keywords: big data analysis, Hadoop MapReduce, analyzing text data, mining Indonesian reviews

Procedia PDF Downloads 185

Authors: Sushma Ghogale

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With a surge in user-generated content or feedback or reviews on the internet, it has become possible and important to know consumers' opinions about products and services. This data is important for both potential customers and businesses providing the services. Data from social media is attracting significant attention and has become the most prominent channel of expressing an unregulated opinion. Prospective customers look for reviews from experienced customers before deciding to buy a product or service. Several websites provide a platform for users to post their feedback for the provider and potential customers. However, the biggest challenge in analyzing such data is in extracting latent features and providing term-level analysis of the data. This paper proposes an approach to use topic modeling to classify the reviews into topics and conduct sentiment analysis to mine the opinions. This approach can analyse and classify latent topics mentioned by reviewers on business sites or review sites, or social media using topic modeling to identify the importance of each topic. It is followed by sentiment analysis to assess the satisfaction level of each topic. This approach provides a classification of hotel reviews using multiple machine learning techniques and comparing different classifiers to mine the opinions of user reviews through sentiment analysis. This experiment concludes that Multinomial Naïve Bayes classifier produces higher accuracy than other classifiers.

Keywords: latent Dirichlet allocation, topic modeling, text classification, sentiment analysis

Procedia PDF Downloads 84

Authors: Sacha Joseph-Mathews, Leili Javadpour

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In the tourism industry, hoteliers spend millions annually on marketing and positioning efforts for their respective hotels, all in an effort to create a specific image in the minds of the consumer. Yet despite extensive efforts to seduce potential hotel guests with sophisticated advertising messages generated by hotel entities, consumers continue to mistrust corporate branding, preferring instead to place their trust in the reviews of their consumer peers. In today’s complex and cluttered marketplace, online reviews can serve as a mediator for consumers who do not have actual knowledge and experiences with the brand, but are in the process of deciding whether or not to engage in a consumption exercise. Traditionally, consumers have used online reviews as a source of comfort and confirmation of a product/service’s positioning. But today, very few customers make any purchase decisions without first researching existing user reviews, making reviews more of a necessity, rather than a luxury in the purchase decision process. The influence of user generated content (UGC) is amplified in the tourism industry; as more than a third of potential hotel guests will not book a room without first reading a review. As corporate branding becomes less relevant and online reviews become more important, how much of the consumer’s stay expectations are being dictated by existing UGC? Moreover, as hotel guest experience a hotel through the lens of an existing review, how much of their stay and in turn their review, would have been influenced by those reviews that they read? Ultimately, there is the potential for UGC to dictate what potential guests will be most critical about, and or most focused on during their stay. If UGC is a stronger influencer in the purchase decision process than corporate branding, doesn’t it have the potential to dictate, the entire stay experience by influencing the expectations of the guest prior to them arriving on the property? For example, if a hotel is an eco-destination and they focus their branding on their website around sustainability and the retreat nature of the hotel. Yet, guest reviews constantly discuss how dissatisfactory the service and food was with no mention of nature or sustainability, will future reviews then focus primarily on the food? Using text analysis software to examine over 25,000 online reviews, we explore the extent to which new reviews are influenced by wording used in previous reviews for a hotel property, versus content generated by corporate positioning. Additionally, we investigate how distinct hotel related UGC is across different types of tourism destinations. Our findings suggest that UGC can have a greater impact on future reviews, than corporate branding and there is more cohesiveness across UGC of different types of hotel properties than anticipated. A model of User Generated Content Influence is presented and the managerial impact of the power of online reviews to trump corporate branding and shape future user experiences is discussed.

Keywords: user generated content, UGC, corporate branding, online reviews, hotels and tourism

Procedia PDF Downloads 69

Authors: Miguel Llorens-Marin, Adolfo Hernandez, Maria Puelles-Gallo

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The increasing influence of Online Travel Agencies (OTAs) on hotel bookings and the electronic word-of-mouth (eWOM) contained in them has been featured by many scientific studies as a major factor in the booking decision. The main reason is that nowadays, in the hotel sector, consumers first come into contact with the offer through the web and the online environment. Due to the nature of the hotel product and the fact that it is booked in advance to actually seeing it, there is a lack of knowledge about its actual features. This makes eWOM a major channel to help consumers to reduce their perception of risk when making their booking decisions. This research studies the relationship between aspects of customer influenceability by reading eWOM communications, at the time of booking a hotel, with the propensity to write a review. In other words, to test relationships between the reading and the writing of eWOM. Also investigates the importance of different underlying motivations for writing eWOM. Online surveys were used to obtain the data from a sample of hotel customers, with 739 valid questionnaires. A measurement model and Path analysis were carried out to analyze the chain of relationships among the independent variable (influenceability from reading reviews) and the dependent variable (propensity to write a review) with the mediating effects of additional variables, which help to explain the relationship. The authors also tested the moderating effects of age and gender in the model. The study considered three different underlying motivations for writing a review on a hotel experience, namely hedonic, altruistic and conflicted. Results indicate that the level of influenceability by reading reviews has a positive effect on the propensity to write reviews; therefore, we manage to link the reading and the writing of reviews. Authors also discover that the main underlying motivation to write a hotel review is the altruistic motivation, being the one with the higher Standard regression coefficient above the hedonic motivation. The authors suggest that the propensity to write reviews is not related to sociodemographic factors (age and gender) but to attitudinal factors such as ‘the most influential factor when reading’ and ‘underlying motivations to write. This gives light on the customer engagement motivations to write reviews. The implications are that managers should encourage their customers to write eWOM reviews on altruistic grounds to help other customers to make a decision. The most important contribution of this work is to link the effect of reading hotel reviews with the propensity to write reviews.

Keywords: hotel reviews, electronic word-of-mouth (eWOM), online consumer reviews, digital marketing, social media

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Authors: Talha Shafiq

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The traditional electricity operation in solar thermal plants is designed to operate on a single path initiating at power plant and executes at the consumer. Due to lack of energy storage facilities during this operation, a decrease in the efficiency is often observed with the power plant performance. This paper reviews the significance of energy storage in supply design and elaborates various methods that can be adopted in this regard which are equally cost effective and environmental friendly. Moreover, various parameters in thermal storage technique are also critically analyzed to clarify the pros and cons in this facility. Discussing the different thermal storage system, their technical and economical evaluation has also been reviewed.

Keywords: thermal energy storage, sensible heat storage, latent heat storage, thermochemical heat storage

Procedia PDF Downloads 539

Authors: Oshin Anand, Atanu Rakshit

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The vast increment in the e-commerce ventures makes this area a prominent research stream. Besides several quantified parameters, the textual content of reviews is a storehouse of many information that can educate companies and help them earn profit. This study is an attempt in this direction. The article attempts to categorize data based on a computed metric that quantifies the influencing capacity of reviews rendering two categories of high and low influential reviews. Further, each of these document is studied to conclude several product feature categories. Each of these categories along with the computed metric is converted to linguistic identifiers and are used in an association mining model. The article makes a novel attempt to combine feature attraction with quantified metric to categorize review text and finally provide frequent patterns that depict customer preferences. Frequent mentions in a highly influential score depict customer likes or preferred features in the product whereas prominent pattern in low influencing reviews highlights what is not important for customers. This is achieved using a hybrid approach of text mining for feature and term extraction, sentiment analysis, multicriteria decision-making technique and association mining model.

Keywords: association mining, customer preference, frequent pattern, online reviews, text mining

Procedia PDF Downloads 368

Authors: Umesh Kumar Soni, Suresh Kumar Soni, S. R. Awasthi

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Worldwide biggest difficulties are climate change, future availability of fossil fuels, and economical feasibility of renewable energy. They force us to use to a greater extent renewable energy and develop suitable hybrid renewable systems. Building heating/cooling consumes significant amount of energy. It can be conserved by use of proper heating/cooling techniques. This paper reviews and critically analyzes various active, passive and hybrid heating/cooling techniques used in green buildings.

Keywords: natural ventilation, energy conservation, hybrid ventilation techniques, climate change

Procedia PDF Downloads 584

Authors: Julie Mariam Abraham, G. J. Melendez-Torres

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Background. Maternal mortality is disproportionately higher in low- and middle- income countries (LMICs) compared to other parts of the world. At the current pace of progress, the Sustainable Development Goals for maternal mortality rate will not be achieved by 2030. A variety of factors influence the increased risk of maternal complications in LMICs. These are exacerbated by socio-economic and political factors, including poverty, illiteracy, and gender inequality. This paper aims to use realist synthesis to identify the contexts, mechanisms, and outcomes (CMOs) of maternal health interventions conducted in LMICs to inform evidence-based practice for future maternal health interventions. Methods. In May 2022, we searched four electronic databases for systematic reviews of maternal health interventions in LMICs published in the last five years. We used open and axial coding of CMOs to develop an explanatory framework for intervention effectiveness. Results. After eligibility screening and full-text analysis, 44 papers were included. The intervention strategies and measured outcomes varied within reviews. Healthcare system level contextual factors were the most frequently reported, and infrastructural capacity was the most reported context. The most prevalent mechanism was increased knowledge and awareness. Discussion. Health system infrastructure must be considered in interventions to ensure effective implementation and sustainability. Healthcare-seeking behaviours are embedded within social and cultural norms, environmental conditions, family influences, and provider attitudes. Therefore, effective engagement with communities and families is important to create new norms surrounding pregnancy and delivery. Future research should explore community mobilisation and involvement to enable tailored interventions with optimal contextual fit.

Keywords: maternal mortality, service delivery and organisation, realist synthesis, sustainable development goals, overview of reviews

Procedia PDF Downloads 57

Authors: Liwen Hou

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The booming mobile business has been penetrating the taxi industry worldwide with P2P (peer to peer) taxi services, as an emerging business model, transforming the industry. Parallel with other mobile businesses, member recommendations and online reviews are believed to be very effective with regard to acquiring new users for P2P taxi services. Based on an empirical dataset of the taxi industry in China, this study aims to reveal which factors influence users’ recommendations and review-writing behaviors. Differing from the existing literature, this paper takes the taxi driver’s perspective into consideration and hence selects a group of variables related to the drivers. We built two models to reflect the factors that influence the number of recommendations and reviews posted on the platform (i.e., the app). Our models show that all factors, except the driver’s score, significantly influence the recommendation behavior. Likewise, only one factor, passengers’ bad reviews, is insignificant in generating more drivers’ reviews. In the conclusion, we summarize the findings and limitations of the research.

Keywords: online recommendation, P2P taxi service, review-writing, word of mouth

Procedia PDF Downloads 293

Authors: Seon-Young Lee, Harkiran Sagoo, Reem Farwana, Katharine Whitehurst, Alex Fowler, Riaz Agha

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Background/Aims: Systematic reviews and meta-analysis are becoming increasingly important way of summarizing research evidence. Researches in ophthalmology may represent further challenges, due to their potential complexity in study design. The aim of our study was to determine the reporting quality of systematic reviews and meta-analysis in ophthalmology with the PRISMA statement, by assessing the articles published between 2010 and 2015 from five major journals with the highest impact factor. Methods: MEDLINE and EMBASE were used to search systematic reviews published between January 2010 and December 2015, in 5 major ophthalmology journals: Progress in Retinal and Eye Research, Ophthalmology, Archives of Ophthalmology, American Journal of Ophthalmology, Journal of the American Optometric Association. Screening, identification, and scoring of articles were performed independently by two teams, followed by statistical analysis including the median, range, and 95% CIs. Results: 115 articles were involved. The median PRISMA score was 15 of 27 items (56%), with a range of 5-26 (19-96%) and 95% CI 13.9-16.1 (51-60%). Compliance was highest in items related to the description of rationale (item 3,100%) and inclusion of a structured summary in the abstract (item 2, 90%), while poorest in indication of review protocol and registration (item 5, 9%), specification of risk of bias affecting the cumulative evidence (item 15, 24%) and description of clear objectives in introduction (item 4, 26%). Conclusion: The reporting quality of systematic reviews and meta-analysis in ophthalmology need significant improvement. While the use of PRISMA criteria as a guideline before journal submission is recommended, additional research identifying potential barriers may be required to improve the compliance to the PRISMA guidelines.

Keywords: systematic reviews, meta-analysis, research methodology, reporting quality, PRISMA, ophthalmology

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Authors: Monika Rezacova

Abstract:

Radiation-induced breast changes are a consequence of radiotherapy toxicity over the breast tissues either related to targeted breast cancer treatment or other thoracic malignancies (eg. lung cancer). This study has created an overview of different changes and their pathophysiology. The main conditions included were skin thickening, interstitial oedema, fat necrosis, dystrophic calcifications, skin retractions, glandular atrophy, breast fibrosis and radiation induced breast cancer. This study has performed focused literature search through multiple databases including pubmed, medline and embase. The study has reviewed English as well as non English publications. As a result of the literature the study provides comprehensive overview of radiation-induced breast changes and their pathophysiology with small focus on new development and prevention.

Keywords: radiotherapy toxicity, breast tissue changes, breast cancer treatment, radiation-induced breast changes

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Authors: Shahram Payandeh

Abstract:

This paper presents an overview of a model which can be used as a part of a decision support system when fusing information from multiple sensing environment. Data fusion has been widely studied in the past few decades and numerous frameworks have been proposed to facilitate decision making process under uncertainties. Multi-sensor data fusion technology plays an increasingly significant role during people tracking and activity recognition. This paper presents an overview of a quantum model as a part of a decision-making process in the context of multi-sensor data fusion. The paper presents basic definitions and relationships associating the decision-making process and quantum model formulation in the presence of uncertainties.

Keywords: quantum model, sensor space, sensor network, decision support

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Authors: Seon-Young Lee, Harkiran Sagoo, Katherine Whitehurst, Georgina Wellstead, Alexander Fowler, Riaz Agha, Dennis Orgill

Abstract:

Introduction: Systematic reviews attempt to answer research questions by synthesising the data within primary papers. They are an increasingly important tool within evidence-based medicine, guiding clinical practice, future research and healthcare policy. We sought to determine the reporting quality of recent systematic reviews in plastic surgery. Methods: This systematic review was conducted in line with the Cochrane handbook, reported in line with the PRISMA statement and registered at the ResearchRegistry (UIN: reviewregistry18). MEDLINE and EMBASE databases were searched in 2013 and 2014 for systematic reviews by five major plastic surgery journals. Screening, identification and data extraction was performed independently by two teams. Results: From an initial set of 163 articles, 79 met the inclusion criteria. The median PRISMA score was 16 out of 27 items (59.3%; range 6-26, 95% CI 14-17). Compliance between individual PRISMA items showed high variability. It was poorest for items related to the use of review protocol (item 5; 5%) and presentation of data on risk of bias of each study (item 19; 18%), while being the highest for description of rationale (item 3; 99%) and sources of funding and other support (item 27; 95%), and for structured summary in the abstract (item 2; 95%). Conclusion: The reporting quality of systematic reviews in plastic surgery requires improvement. ‘Hard-wiring’ of compliance through journal submission systems, as well as improved education, awareness and a cohesive strategy among all stakeholders is called for.

Keywords: PRISMA, reporting quality, plastic surgery, systematic review, meta-analysis

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Authors: Arvind Dhingra, Ashwani Kumar Sharma

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Power quality is an important parameter for today’s consumers. Various custom power devices are in use to give a proper supply of power quality. Dynamic Voltage Restorer is one such custom power device. DVR is a static VAR device which is used for series compensation. It is a power electronic device that is used to inject a voltage in series and in synchronism to compensate for the sag in voltage. Inductive Loads are a major source of power quality distortion. The induction furnace is one such typical load. A typical induction furnace is used for melting the scrap or iron. At the time of starting the melting process, the power quality is distorted to a large extent especially with the induction of harmonics. DVR is one such approach to mitigate these harmonics. This paper is an attempt to overview the various control strategies being followed for control of power quality by using DVR. An overview of control of harmonics using DVR is also presented.

Keywords: DVR, power quality, harmonics, harmonic mitigation

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Authors: Imen Douzi, Karim Ben Kahla

Abstract:

In spite of the growing attention for social innovation, it is still considered to be in a stage of infancy with minimal progress in theory development. Upon examining the field of study, one would have to conclude that, over the past two decades, academic research has focused primarily on establishing a conceptual foundation. This has resulted in a considerable stream of conceptual papers which have outnumbered empirical articles. Nevertheless, despite its growing popularity, scholars and practitioners are far from reaching a consensus as to what social innovation actually means which resulted in competing definitions and approaches within the field of social innovation and lack of unifying conceptual framework. This paper reviews empirical research studies on social innovation, classifies them along three dimensions and summarizes research findings for each of these dimensions. Preliminary to the analysis of empirical researches, an overview of different perspectives of social innovation is presented.

Keywords: analysis of empirical research, definition, empirical research, social innovation perspectives

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Authors: Claudia Mertens, Amanda Shufflebarger

Abstract:

Step one: What we know about effective learning for pupils with SEN: results of 2 systematic reviews: Before establishing principles and practices for teaching and learning of pupils with SEN, we need a good overview of the results of empirical studies conducted in the respective field. Therefore, two systematic reviews on the use of digital tools in inclusive and non-inclusive school settings were conducted - taking into consideration studies published in German: One systematic review included studies having undergone a peer review process, and the second included studies without peer review). The results (collaboration of two German universities) will be presented during the conference. Step two: Students’ results of a research lab on “inclusive media education”: On this basis, German students worked on “inclusive media education” in small research projects (duration: 1 year). They were “education majors” enrolled in a course on inclusive media education. They conducted research projects on topics ranging from smartboards in inclusive settings, digital media in gifted math education, Tik Tok in German as a Foreign Language education and many more. As part of their course, the German students created an academic conference poster. In the conference, the results of these research projects/papers are put into the context of the results of the systematic reviews. Step three: Global Classroom: The German students’ posters were critically discussed in a global classroom in cooperation with Indiana University East (USA) and Hamburg University (Germany) in the winter/spring term of 2022/2023. 15 students in Germany collaborated with 15 students at Indiana University East. The IU East student participants were enrolled in “Writing in the Arts and Sciences,” which is specifically designed for pre-service teachers. The joint work began at the beginning of the Spring 2023 semester in January 2023 and continued until the end of the Uni Hamburg semester in February 2023. Before January, Uni Hamburg students had been working on a research project individually or in pairs. Didactic Approach: Both groups of students posted a brief video or audio introduction to a shared Canvas discussion page. In the joint long synchronous session, the students discussed key content terms such as inclusion, inclusive, diversity, etc., with the help of prompt cards, and they compared how they understood or applied these terms differently. Uni Hamburg students presented drafts of academic posters. IU East students gave them specific feedback. After that, IU East students wrote brief reflections summarizing what they learned from the poster. After the class, small groups were expected to create a voice recording reflecting on their experiences. In their recordings, they examined critical incidents, highlighting what they learned from these incidents. Major results of the student research and of the global classroom collaboration can be highlighted during the conference. Results: The aggregated results of the two systematic reviews AND of the research lab/global classroom can now be a sound basis for 1) improving accessibility for students with SEN and 2) for adjusting teaching materials and concepts to the needs of the students with SEN - in order to create successful learning.

Keywords: digitalization, inclusion, inclusive media education, global classroom, systematic review

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