bluuebunny/crossref_metadata_2025 huggingface dataset:
Mild intermittent hypoxia exposure alters gut microbiota composition in men with overweight and obesity
Authors: Van Meijel R.L.J. , Venema K. , Canfora E.E. , Blaak E.E. , Goossens G.H.
Published: July 2022

Results from high altitude studies in humans and controlled animal experiments suggest that hypoxia exposure induces alterations in gut microbiota composition, which may in turn affect host metabolism. However, well-controlled studies investigating the effects of normobaric hypoxia exposure on gut microbiota composition in humans are lacking. The aim of this study was to explore the impact of mild intermittent hypoxia (MIH) exposure on gut microbiota composition in men with overweight and/or obesity. We performed a randomised, single-blind crossover study, in which participants were exposed to MIH (FiO2: 15%, 3×2 h per day) and normoxia (FiO2: 21%) for seven consecutive days. Following the MIH and normoxia exposure regimens, faecal samples were collected for determination of faecal microbiota composition using 16S rRNA gene-amplicon sequencing in the morning of day 8. Paired faecal samples were available for five individuals. Furthermore, tissue-specific insulin sensitivity was determined using the gold-standard two-step hyperinsulinemic-euglycemic clamp. MIH did not affect microbial alpha and beta-diversity but reduced the relative abundance of Christensenellaceae and Clostridiaceae bacterial families. MIH significantly increased the abundances of obligate anaerobic bacterial genera including Fusicatenibacter, Butyricicoccus and Holdemania, whilst reducing Christensenellaceae R-7 group and Clostridium sensu stricto 1, although these findings were not statistically significant after correction for multiple testing. Furthermore, MIH-induced alterations in abundances of several genera were associated with changes in metabolic parameters such as adipose and peripheral insulin sensitivity, plasma levels of insulin, fatty acids, triacylglycerol and lactate, and substrate oxidation. In conclusion, we demonstrate for the first time that MIH exposure induces modest effects on faecal microbiota composition in humans, shifting several bacterial families and genera towards higher abundances of anaerobic butyrate-producing bacteria. Moreover, MIH-induced effects on faecal microbial composition were associated with parameters related to glucose and lipid homeostasis, supporting a link between MIH-induced alterations in faecal microbiota composition and host metabolism.

The study was registered at the Netherlands Trial Register: NL7120/NTR7325.
Feeding black soldier fly larvae (Hermetia illucens) reared on organic rest streams alters gut characteristics of Atlantic salmon (Salmo salar)
Authors: Leeper A. , Benhaïm D. , Smárason B.Ö. , Knobloch S. , Òmarsson K.L. , Bonnafoux T. , Pipan M. , Koppe W. , Björnsdóttir R. , Øverland M.
Published: July 2022

The Atlantic salmon (Salmo salar) aquaculture industry is growing, and with it, the need to source and optimise sustainable ingredients for aquafeeds. Black soldier fly (BSF) larvae (Hermetia illucens) have received increasing research attention since they are a good source of protein that can efficiently convert a wide range of low-value organic material into valuable resources. This study investigated the impact of three differently processed BSF meals, an untreated BSF diet (BSFC+), a dechitinated BSF diet (BSFC-) and a fermented BSF diet (BSFC+P+) at a 10% inclusion level replacing fish meal in a fish meal control (FM) and a marine and soy protein concentrate based control diet (SPC). Growth performance, gut microbiome and gut histology of salmon fry was assessed. The inclusion and processing methods of BSF showed no adverse impacts on either growth performance or gut histology. However, the gut microbiome of fish was significantly altered by both the protein source and the processing method of the BSF larvae. Fish fed BSFC+, had an increased diversity and evenness of the community compared with conventional protein sources alone, and compared with the other BSF processing methods. However, control diets had a greater presence of lactic acid bacteria and genera associated with faster growing hosts. Fish fed BSF had a high relative abundance of the genus, Exiguobacterium, a chitin-degrading bacterium and in BSFC+P+ fed fish this bacterium completely dominated the community, indicating the presence of dysbiosis. Future studies should determine, why Exiguobacterium has dominated the community for the BSFC+P+ diet, and if it provides a digestive function to the host and identify bacteria that are indicators of optimal host performance and resilience. The results confirmed that BSF is a promising fish meal replacement for salmon, and it demonstrated that BSFC+ has a potential prebiotic impact on the gut microbiome of Atlantic salmon.
Energy conservation for the compressible ideal Hall-MHD equations
Authors: Zhou Yanping , Deng Xuemei , Bie Qunyi , Kang Lingping
Published: July 2022

In this paper, we study the regularity and energy conservation of the weak solutions for compressible ideal Hall-magnetohydrodynamic (Hall-MHD) system, where $ (t, x)\in(0, T)\times {\mathbb{T}}^d(d\geq\; 1) $. By exploring the special structure of the nonlinear terms in the model, we obtain the sufficient conditions for the regularity of the weak solutions for energy conservation. Our main strategy relies on commutator estimates.
Minimal homothetical and translation lightlike graphs in $ \mathbb{R} _{q}^{n+2} $
Authors: Sağlam Derya
Published: July 2022

In this paper, homothetical and translation lightlike graphs, which are generalizations of homothetical and translation lightlike hypersurfaces are investigated in the semi-Euclidean space $ \mathbb{R}_{q}^{n+2} $, respectively. We prove that all homothetical and all translation lightlike graphs are locally the hyperplanes. According to this fact, both of these graphs are minimal.
Instability analysis and geometric perturbation theory to a mutual beneficial interaction between species with a higher order operator
Authors: Palencia José Luis Díaz , Otero Abraham
Published: July 2022

The higher order diffusion can be understood as a generalization to the classical fickian diffusion. To account for such generalization, the Landau-Ginzburg free energy concept is applied leading to a fourth order spatial operator. This kind of diffusion induces a set of instabilities in the proximity of the critical points raising difficulties to study the convergence of Travelling Waves (TW) solutions. This paper aims at introducing a system of two species driven by a mutual interaction towards prospering and with a logistic term in their respective reactions. Previous to any analytical finding of TW solutions, the instabilities of such solutions are studied. Afterwards, the Geometric Perturbation Theory is applied to provide means to search for a linearized hyperbolic manifold in the proximity of the equilibrium points. The homotopy graphs for each of the flows to the hyperbolic manifolds are provided, so that analytical solutions can be obtained in the proximity of the critical points. Additionally, the set of eigenvalues in the homotopy graphs tend to cluster and synchronize for increasing values of the TW-speed.
A simple model to estimate the transmissibility of the Beta, Delta, and Omicron variants of SARS-COV-2 in South Africa
Authors: Yu Yangyang , Liu Yuan , Zhao Shi , He Daihai
Published: July 2022

The COVID-19 pandemic caused multiple waves of mortality in South Africa, where three genetic variants of SARS-COV-2 and their ancestral strain dominated consecutively. State-of-the-art mathematical modeling approach was used to estimate the time-varying transmissibility of SARS-COV-2 and the relative transmissibility of Beta, Delta, and Omicron variants. The transmissibility of the three variants were about 73%, 87%, and 276% higher than their preceding variants. To the best of our knowledge, our model is the first simple model that can simulate multiple mortality waves and three variants' replacements in South Africa. The transmissibility of the Omicron variant is substantially higher than that of previous variants.
The impact of business conditions and commodity market on US stock returns: An asset pricing modelling experiment
Authors: Huang Fangzhou , Song Jiao , Taylor Nick J.
Published: July 2022

In this paper, two comprehensive mathematical approaches: cubic piecewise polynomial function (CPPF) model and the Fourier Flexible Form (FFF) model are built into asset pricing models to explore the stock market risk, commodity market risk and overall business conditions in relation to US stock returns as a modelling experiment. A selection of knots and orders are applied on the models to determine the best fit coefficients, respectively, based on Akaike Information Criteria (AIC). The classic risk coefficient along with downside and upside counterparts are estimated in a non-linear time-weighted fashion and are subsequently adopted as risk factors to investigate the explanatory and predictive power to stock returns. It is found that time-weighted classic, downside and upside risk coefficients of all three domains provide significant explanatory power to current stock returns, while the predictive power appears to be weak. The findings fill the gap in literature, specifically on both investigating and pricing the time-weighted risk. This paper innovatively employs the Aruoba-Diebold-Scotti (ADS) real business index to measure the business conditions in macroeconomics context. The methodology proposed in this paper embeds advanced mathematical approaches to provide robust regression estimation. The application of proposed models enriches the dimension in pricing risk in stock market and wider financial market.
Il contributo delle fonti epigrafiche alla conoscenza della topografia dell’Urbe: novità, problemi e metodi
Authors: Gregori Gian Luca , Orlandi Silvia
Published: July 2022

Il contributo si articola in due parti: nella prima, viene fatta una panoramica che, senza la pretesa di essere esaustiva, esemplifica i vari modi in cui l’epigrafia, negli ultimi 30 anni, ha contribuito a migliorare le nostre conoscenze sull’esistenza, la localizzazione e le vicende storiche di molti aspetti della topografia di Roma antica; nella seconda, ci si concentra sul problema della localizzazione – su base epigrafica – delle domus e delle attività commerciali, cogliendo lo spunto da due nuovi documenti di recente pubblicazione.
Approvvigionamento, infrastruttura, trasporti
Authors: Bruun Christer
Published: July 2022

Il presente contributo riguarda l’approvvigionamento di Roma durante il Principato. Le recenti scoperte archeologiche nelle immediate vicinanze della città di Roma forniscono nuove informazioni sulle risorse idrauliche e sulla tecnologia (in particolare i dispositivi per prelevare l’acqua) a disposizione della popolazione. La maggior parte delle importazioni a Roma sono state trasportate sul Tevere, e ci sono nuove informazioni sulla produzione di mattoni a monte di Roma, mentre altre nuove testimonianze riguardano l’importazione di legna da ardere dal paese sabino. Soprattutto Roma era rifornita da importazioni che arrivavano a Ostia-Porto e venivano portate a Roma sul Tevere in piccole imbarcazioni (naues caudicariae). Il viaggio fino a Roma durava tre giorni e organizzare il traffico del Tevere era una grande sfida per il governo imperiale, la cui complessità non è sempre pienamente percepita. Il compito è stato evidentemente gestito con successo, poiché Roma e la sua popolazione sono sopravvissuti. L’articolo conclude che, nel valutare la popolazione totale di Roma, è importante comprendere i vincoli che l’alzaia lungo il Tevere rappresentava per il volume di merci che potevano essere trasportate fino a Roma.
Key Pillars for Digital Transformation of the Developing World
Authors: Chengetanai Gibson , Chikati Ronald
Published: July 2022

Digital transformation is happening at a considerable rate in the developing world; however, its adoption seems higher in the developed world. Therefore, this chapter aims to present the key drivers or pillars that make up digital transformation in developing countries. The chapter argued that strategy, technology, and innovation are the broad categories that influence digital transformation in any country, whether developing or developed. Also, the chapter articulates what has been happening in the developing world, focusing on Southern Africa to achieve digital transformation. A framework for digital transformation that consists of three broad pillars strategy, technology, and innovation was proposed. Lastly, the chapter proposed that future researchers on digital transformation can focus on the broad pillars of digital transformation.
Do Gender and Department Make a Difference in Achievement Goal Orientations of Turkish Prospective Teachers
Authors: Bezen Sevim , Demirkasımoğlu Nihan
Published: July 2022

This study aims to determine the achievement goal orientation of prospective Turkish teachers in terms of department and gender variables. The research was a cross-sectional study with 335 prospective teachers studying nine different teaching programs. Achievement goal orientations scale was used as a data collection tool. Descriptive statistical methods, one-way ANOVA, Tukey, and independent groups t-test were used in data analysis. A significant difference was determined among female and male prospective teachers' learning goal orientation and performance-avoidance goal orientation. The average of prospective female teachers in learning goal orientation was higher, while the average of male teacher candidates was higher in the dimension of performance-avoidance goal orientation. The learning goal orientations of the prospective teachers show a significant difference between the science teaching and mathematics teaching departments. Accordingly, science teachers have higher scores.
Real Time Sentiment Analysis
Authors: Palit Sandip , Ghosh Soumadip
Published: July 2022

Data is the most valuable resource. We have a lot of unstructured data generated by the social media giants Twitter, Facebook, and Google. Unfortunately, analytics on unstructured data cannot be performed. As the availability of the internet became easier, people started using social media platforms as the primary medium for sharing their opinions. Every day, millions of opinions from different parts of the world are posted on Twitter. The primary goal of Twitter is to let people share their opinion with a big audience. So, if the authors can effectively analyse the tweets, valuable information can be gained. Storing these opinions in a structured manner and then using that to analyse people's reactions and perceptions about buying a product or a service is a very vital step for any corporate firm. Sentiment analysis aims to analyse and discover the sentiments behind opinions of various people on different subjects like commercial products, politics, and daily societal issues. This research has developed a model to determine the polarity of a keyword in real time.
Deep Learning for Sentiment Analysis
Authors: Karas Vincent , Schuller Björn W.
Published: July 2022

Sentiment analysis is an important area of natural language processing that can help inform business decisions by extracting sentiment information from documents. The purpose of this chapter is to introduce the reader to selected concepts and methods of deep learning and show how deep models can be used to increase performance in sentiment analysis. It discusses the latest advances in the field and covers topics including traditional sentiment analysis approaches, the fundamentals of sentence modelling, popular neural network architectures, autoencoders, attention modelling, transformers, data augmentation methods, the benefits of transfer learning, the potential of adversarial networks, and perspectives on explainable AI. The authors' intent is that through this chapter, the reader can gain an understanding of recent developments in this area as well as current trends and potentials for future research.
Sentiment Analysis Techniques, Tools, Applications, and Challenge
Authors: Dhawale Chitra A. , Chaudhari Vandana V.
Published: July 2022

Sentiment (opinion) refers to the feelings of a human being, which are generally reflected through speech and writing in a particular natural language. The analysis of these sentiments are therefore carried with the help of natural language processing, text analysis, and computational linguistics to identify and extract subjective information in source materials. Generally speaking, sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document. Sentiment analysis is widely applied to reviews and social media for a variety of applications, ranging from marketing research, political reviews, policy making, decision making, customer service, etc. In this chapter the authors include the introduction to sentiment analysis, various approaches for classification of sentiment analysis, various tools used, the application areas, challenges, and future research direction in this most demanding area.
A Comparative Study of Different Classification Techniques for Sentiment Analysis
Authors: Ghosh Soumadip , Hazra Arnab , Raj Abhishek
Published: July 2022

Sentiment analysis denotes the analysis of emotions and opinions from text. The authors also refer to sentiment analysis as opinion mining. It finds and justifies the sentiment of the person with respect to a given source of content. Social media contain vast amounts of the sentiment data in the form of product reviews, tweets, blogs, and updates on the statuses, posts, etc. Sentiment analysis of this largely generated data is very useful to express the opinion of the mass in terms of product reviews. This work is proposing a highly accurate model of sentiment analysis for reviews of products, movies, and restaurants from Amazon, IMDB, and Yelp, respectively. With the help of classifiers such as logistic regression, support vector machine, and decision tree, the authors can classify these reviews as positive or negative with higher accuracy values.
Approaches to Sentiment Analysis on Product Reviews
Authors: Vyas Vishal , Uma V.
Published: July 2022

Purchase decisions are better when opinions/reviews about products are considered. Similarly, reviewing customer feedback help in improving the sale and ultimately benefit the business. Web 2.0 provides various platforms such as Twitter, Facebook, etc. where one can comment, review, or post to express his/her happiness, anger, disbelief, sadness toward products, people, etc. To computationally analyze the sentiments in text requires a better understanding of the technologies used in sentiment analysis. This chapter gives a comprehensive understanding about the techniques used in sentiment analysis. Machine learning approaches are mostly used for sentiment analysis. Whereas, as per the text and required results, lexicon-based approaches are also used for the same purpose. This chapter includes the discussion on the evaluation parameters for the sentiment analysis. This chapter would also highlight ontology approach for sentiment analysis and outstanding contributions made in this field. Keywords: Sentiment Analysis, Product reviews, Supervised learning, Unsupervised learning, Social networking websites, Ontology
Towards a Sentiment Analysis Model Based on Semantic Relation Analysis
Authors: Tran Thien Khai , Phan Tuoi Thi
Published: July 2022

Sentiment analysis is an important new field of research that has attracted the attention not only of researchers, but also businesses and organizations. In this article, the authors propose an effective model for aspect-based sentiment analysis for Vietnamese. First, sentiment dictionaries and syntactic dependency rules were combined to extract reliable word pairs (sentiment - aspect). They then relied on ontology to group these aspects and determine the sentiment polarity of each. They introduce two novel approaches in this work: 1) in order to “smooth” the sentiment scaling (rather than using discrete categories of 1, 0, and -1) for fined-grained classification, then extract multi-word sentiment phrases instead of sentiment words, and 2) the focus is not only on adjectives but also nouns and verbs. Initial evaluations of the system using real reviews show promising results.
Analyzing Social Emotions in Social Network Using Graph Based Co-Ranking Algorithm
Authors: Priya Kani , Krishnaveni R.  , Krishnamurthy M.  , Bairavel S.
Published: July 2022

Twitter has become exceedingly popular, with hundreds of millions of tweets being posted every day on a wide variety of topics. This has helped make real-time search applications possible with leading search engines routinely displaying relevant tweets in response to user queries. Recent research has shown that a considerable fraction of these tweets are about “events,” and the detection of novel events in the tweet-stream has attracted a lot of research interest. However, very little research has focused on properly displaying this real-time information about events. For instance, the leading search engines simply display all tweets matching the queries in reverse chronological order. Online content exhibits rich temporal dynamics, and diverse real-time user generated content further intensifies this process. However, temporal patterns by which online content grows and fades over time, and by which different pieces of content compete for attention remain largely unexplored. This article describes tracking and analyzing public sentiment on social networks and finding the possible reasons causing these variations. It is important to find the decision from public views and opinion in different domain. They can be used to discover special topics or aspects in one text collection in comparison with another background text collection. The implemented method attains the 95% accuracy while predict the sentiments from the social websites and the 96.3% of the opinion rate with minimum time.
Method to Rank Academic Institutes by the Sentiment Analysis of Their Online Reviews
Authors: Sidhu Simran , Khurana Surinder Singh
Published: July 2022

A large number of reviews are expressed on academic institutes using the online review portals and other social media platforms. Such reviews are a good potential source for evaluating the Indian academic institutes. This chapter aimed to collect and analyze the sentiments of the online reviews of the academic institutes and ranked the institutes on the basis of their garnered online reviews. Lexical-based sentiment analysis of their online reviews is used to rank academic institutes. Then these rankings were compared with the NIRF PR Overall University Rankings List 2017. The outcome of this work can efficiently support the overall university rankings of the NIRF ranking list to enhance NIRF's public perception parameter (PRPUB). The results showed that Panjab University achieved the highest sentiment score, which was followed by BITS-Pilani. The results highlighted that there is a significant gap between NIRF's perception rankings and the perception of the public in general regarding an academic institute as expressed in online reviews.
Develop a Neural Model to Score Bigram of Words Using Bag-of-Words Model for Sentiment Analysis
Authors: Balamurali Anumeera , Ananthanarayanan Balamurali
Published: July 2022

A Bag-of-Words model is widely used to extract the features from text, which is given as input to machine learning algorithm like MLP, neural network. The dataset considered is movie reviews with both positive and negative comments further converted to Bag-of-Words model. Then the Bag-of-Word model of the dataset is converted into vector representation which corresponds to a number of words in the vocabulary. Each word in the review documents is assigned with a score and the scores are later represented in vector representation which is later fed as input to neural model. In the Kera's deep learning library, the neural models will be simple feedforward network models with fully connected layers called ‘Dense'. Bigram language models are developed to classify encoded documents as either positive or negative. At first, reviews are converted to lines of token and then encoded to bag-of-words model. Finally, a neural model is developed to score bigram of words with word scoring modes.
Deep Learning Based Sentiment Analysis for Phishing SMS Detection
Authors: Sharaff Aakanksha , Allenki Ramya , Seth Rakhi
Published: July 2022

Sentiment analysis works on the principle of categorizing and identifying the text-based content and the process of classifying documents into one of the predefined classes commonly known as text classification. Hackers deploy a strategy by sending malicious content as an advertisement link and attack the user system to gain information. For protecting the system from this type of phishing attack, one needs to classify the spam data. This chapter is based on a discussion and comparison of various classification models that are used for phishing SMS detection through sentiment analysis. In this chapter, SMS data is collected from Kaggle, which is classified as ham or spam; while implementing the deep learning techniques like Convolutional Neural Network (CNN), CNN with 7 layers, and CNN with 11 layers, different results are generated. For evaluating these results, different machine learning techniques are used as a baseline algorithm like Naive Bayes, Decision Trees, Support Vector Machine (SVM), and Artificial Neural Network (ANN). After evaluation, CNN showed the highest accuracy of 99.47% as a classification model.
Social Big Data Mining
Authors: Rodrigues Anisha P. , Chiplunkar Niranjan N. , Fernandes Roshan
Published: July 2022

Social media is used to share the data or information among the large group of people. Numerous forums, blogs, social networks, news reports, e-commerce websites, and many more online media play a role in sharing individual opinions. The data generated from these sources is huge and in unstructured format. Big data is a term used for data sets that are large or complex and that cannot be processed by traditional processing system. Sentimental analysis is one of the major data analytics applied on big data. It is a task of natural language processing to determine whether a text contains subjective information and what information it expresses. It helps in achieving various goals like the measurement of customer satisfaction, observing public mood on political movement, movie sales prediction, market intelligence, and many more. In this chapter, the authors present various techniques used for sentimental analysis and related work using these techniques. The chapter also presents open issues and challenges in sentimental analysis landscape.
Using Sentiment Analysis for Evaluating e-WOM
Authors: Canbolat Zehra Nur , Pinarbasi Fatih
Published: July 2022

Electronic word of mouth is one of the keys elements for marketing decision making. e-WOM has been focus of marketing research as technology and social media become larger part of consumers' lives. This study set out to examine e-wom concept with sentiment analysis methodology in service industry context. The structure of study is twofold including theoretical backgound of related concepts and application section. Theoretical background section contains electronic word of mouth, new consumer and sentiment analysis concepts, and included selected studies for sentiment analysis. The application section which this study has focus on includes a three-stage plan for sentiment analysis practices. Each stage has three different scenarios. One algorithm and one real-life application for each stage are included. Nine scenarios for different service organizations imply that sentiment analysis supported with other methodologies can contribute to understanding of electronic word of mouth.
Opinion Mining in Tourism
Authors: Özen Ibrahim Akın , Ilhan Ibrahim
Published: July 2022

In the tourism sector, online tourist reviews analysis is one of the methods to evaluate the products and services offered by businesses and understand the needs of tourists. These reviews take place in social networks and e-commerce sites in parallel with the developments in information and communication technologies. Tourists generate these reviews during or after their use of the products or services. In the literature, these reviews are referred to as UGC (User Generated Content) or eWOM (electronic word-of-mouth). The scientific evaluation of the textual contents in tourist reviews is done by text mining, which is a sub-area of data mining. This chapter discusses the methods and techniques of opinion mining or sentiment analysis. In addition, aspect-based sentiment analysis and techniques to be used in the application are discussed. A case study was carried out using aspect-based sentiment analysis method. In the application “Cappadocia home cooking” restaurant used tourist reviews.
The Application of Sentiment Analysis and Text Analytics to Customer Experience Reviews to Understand What Customers Are Really Saying
Authors: Gallagher Conor , Furey Eoghan , Curran Kevin
Published: July 2022

In a world of ever-growing customer data, businesses are required to have a clear line of sight into what their customers think about the business, its products, people and how it treats them. Insight into these critical areas for a business will aid in the development of a robust customer experience strategy and in turn drive loyalty and recommendations to others by their customers. It is key for business to access and mine their customer data to drive a modern customer experience. This article investigates the use of a text mining approach to aid sentiment analysis in the pursuit of understanding what customers are saying about products, services and interactions with a business. This is commonly known as Voice of the Customer (VOC) data and it is key to unlocking customer sentiment. The authors analyse the relationship between unstructured customer sentiment in the form of verbatim feedback and structured data in the form of user review ratings or satisfaction ratings to explore the question of whether customers say what they really think when given the opportunity to provide free text feedback as opposed to how they rate a product on a scale of one to five. Using various Sentiment Analysis approaches, the authors assign a sentiment score to a piece of verbatim feedback and then categorise it as positive, negative, or neutral. Using this normalised sentiment score, they compare it to the corresponding rating score and investigate the potential business insights. The results obtained indicate that a business cannot rely solely on a standalone single metric as a source of truth regarding customer experience. There is a significant difference between the customer ratings score and the sentiment of their corresponding review of the product. The authors propose that it is imperative that a business supplements their customer feedback scores with a robust sentiment analysis strategy.
eWOW of Guests Regarding Their Hotel Experience
Authors: Breda Zelia , Costa Rui , Dinis Gorete , Martins Amandine Angie
Published: July 2022

Online comments are increasingly mentioned as an important source of information, simplifying consumers' buying decisions. Online user-generated content has become one of the main sources of information for tourists, who themselves become creators of their own online content. This chapter focuses on sentiment analysis of comments made on TripAdvisor regarding one resort located in the Algarve region, in Portugal. The resort has good reviews, which means that the eWOM is positive. The highest scores relate to the resort's cleanliness, location and quality of sleep, and those that were less relevant were the value for money, the rooms and the service. The most dominant emotion is joy, followed by an analytical response. Negative emotions, such as sadness and anger, were not found very often in the online reviews. These results could be explained by the quality of the service, the kindness of the staff, the facilities for children, the entertainment, and the location, attributes that were often highlighted in the comments.
Multimodal Sentiment Analysis
Authors: Kaur Ramandeep , Kautish Sandeep
Published: July 2022

Multimodal sentiments have become the challenge for the researchers and are equally sophisticated for an appliance to understand. One of the studies that support MS problems is a MSA, which is the training of emotions, attitude, and opinion from the audiovisual format. This survey article covers the comprehensive overview of the last update in this field. Many recently proposed algorithms and various MSA applications are presented briefly in this survey. The article is categorized according to their contributions in the various MSA techniques. The main purpose of this survey is to provide a full image of the MSA opportunities and difficulties and related field with brief details. The main contribution of this article includes the sophisticated categorizations of a large number of recent articles and the illustration of the recent trend of research in the MSA and its related areas.
Microblog Sentiment Analysis Using User Similarity and Interaction-Based Social Relations
Authors: Mi Chuanmin , Ruan Xiaoyan , Xiao Lin
Published: July 2022

With the rapid development of information technology, microblog sentiment analysis (MSA) has become a popular research topic extensively examined in the literature. Microblogging messages are usually short, unstructured, contain less information, creating a significant challenge for the application of traditional content-based methods. In this study, the authors propose a novel method, MSA-USSR, in which user similarity information and interaction-based social relations information are combined to build sentiment relationships between microblogging data. They make use of these microblog–microblog sentiment relations to train the sentiment polarity classification classifier. Two Sina-Weibo datasets were utilized to verify the proposed model. The experimental results show that the proposed method has a better sentiment classification accuracy and F1-score than the content-based support vector machine (SVM) method and the state-of-the-art supervised model known as SANT.
Social Media and Children
Authors: Ersoy Mustafa
Published: July 2022

As a result of high-tech developments and the increase in the importance of the global communication, social media websites and applications have occurred as a new way of communication and self-expression in the contemporary world. Globalization has forced people to obtain and spread the necessary information quickly, and due to this requirement, people of all ages have had to acquire digital skills which they utilize to meet their need of learning and being informed about the issues happening around the world. Social media tools and applications are being highly and commonly used all round the world by all kinds of people from all ages in order to express themselves, get to know other people, share their opinions and learn others' opinions on the world issues, socialize, and have fun. Regarding its effects on children, social media has both advantages and disadvantages.
The Facebook Me
Authors: Zhang Heng , Dunn Robert Andrew
Published: July 2022

For a better understanding of social networking site usage, the present study examines the influence of gender, personality, and self-esteem on social media presentation. The researchers found that extroverted women posted more Facebook pictures than extroverted men did. Neuroticism was related to self-presentation, and agreeableness is related to Facebook friends. Lower self-esteem was related to more self-presentation on Facebook. Women were more likely to post gender role expressions than men were. And higher levels of neuroticism were related to greater gender role expressions.
Facebook Communities of African Diasporas and Their U.S. Embassies
Authors: Mesbah Hesham , Cooper Lauren
Published: July 2022

This study explores how the Nigerian, Ethiopian, and Egyptian diasporas in the United States use their Facebook groups to create their imagined communities. It also draws a parallel between their use of Facebook and how the embassies of their countries of origin use the same platform in performing their official duties. Six hundred Facebook posts drawn for the groups and the embassies were content-analyzed for this study. The results show that the three African diaspora groups have more pragmatic uses of their Facebook communities, such as the exchange of services, advice and information on day-to-day living, while their embassies use the platform more for public relations objectives in planning their official communication that emphasizes nation-branding, the promotion of their various countries, and for other diplomatic chores.
Follow my Snaps!
Authors: Chapin John R
Published: July 2022

Using third-person perception as a theoretical framework, a survey of 1,167 American adolescents explores their social media use and its relationship to verbal, emotional, physical, and sexual abuse. Despite the sexual nature of social media platforms like Snapchat, which are popular with adolescents, even adolescents who have experienced sexual violence in the past. Snapchat users were more likely than non-users to report abusive behavior to others. Adolescents exhibited third-person perception, believing others were more affected than they were by negative social media posts. This was related to experience with violence, and social media use. A third-person effect emerged, as adolescents who exhibit third-person perception were more likely to engage in abusive behaviors, both face-to-face and in an electronic medium.
Profiling the Users of High Influence on Social Media in the Context of Public Events
Authors: An Lu , Hu Junyang , Xu Manting , Li Gang , Yu Chuanming
Published: July 2022

The highly influential users on social media platforms may lead the public opinion about public events and have positive or negative effects on the later evolution of events. Identifying highly influential users on social media is of great significance for the management of public opinion in the context of public events. In this study, the highly influential users of social media are divided into three types (i.e., topic initiator, opinion leader, and opinion reverser). A method of profiling highly influential users is proposed based on topic consistency and emotional support. The event of “Jiankui He Editing the Infants' Genes” was investigated. The three types of users were identified, and their opinion differences and dynamic evolution were revealed. The comprehensive profiles of highly influential users were constructed. The findings can help emergency management departments master the focus of attention and emotional attitudes of the key users and provide the method and data support for opinion management and decision-making of public events.
Loneliness, Disclosure, and Facebook Usage
Authors: Lee Fung Yin , Webb Lynne M.
Published: July 2022

The authors conducted an online survey of 241 emerging adults in Hong Kong, China to assess potential associations between loneliness, Facebook usage, and self-disclosure on Facebook. Loneliness was not associated with Facebook usage, but rather inversely related with negative disclosure; the lonelier the Facebook user, the less he/she disclosed negative information. The pattern of associations between Facebook usage and self-disclosure indicted that the more time users spent on Facebook, the more they revealed positive disclosures and the less they revealed negative disclosures. The authors argue that these findings may provide evidence of a “remain positive” norm among emerging adult Facebook users in Hong Kong. They note that their findings may be unique to their cultural context.
Market Economy and Good Living
Authors: Luque González Arturo , Guamán Leonor Karina , Popescu Cristina Raluca Gh.
Published: July 2022

There is currently an economic metamorphosis underway that involves myriad (mis)development processes. At the same time, processes of inequality are emerging, imbued with their own historical context. This study evaluated the eco-social program known as Good Living (Buen Vivir, Sumak Kawsay) in Ecuador as a tool for change for the most vulnerable sectors that are intrinsically connected to their culture and customs. The study also examined the parallel processes of inequality and the excessive protection of private interests that favor a new world order driven by the maximization of profit. With this objective, the current state of the processes associated with Good Living in the Ecuadorian province of Orellana was analyzed through interviews with relevant local representatives of institutional life. The results highlight the abandonment of the processes of the solidarity and social economy and the resurgence, both by action and omission, of an extractivist model far removed from the principles of compassion, inclusion, and social participation.
Current High-Powered Challenges and High-Reaching Reforms
Authors: Popescu Cristina Raluca Gh. , González Arturo Luque
Published: July 2022

Knowledge has the miraculous power to advance the United Nations Sustainable Development Goals (SDGs) at an international level, with the notable help provided by courageous reforms due to promoting a new economic model based on quality, green energy, digitalization, and shock resistance. Environmental sustainability relies on collaboration in achieving the SDGs and on communication in making the SDGs a way of living. The unforgettable challenges brought in today's society by the COVID-19 pandemic and the COVID-19 crisis posed even a greater pressure than before to achieve a better and more sustainable future for all, thus placing on pivotal positions the answers for the following questions: “What steps are due to be taken for ensuring affordable and clean energy?” “What role do sustainable cities and communities play in people's lives?” “What does climate action involve in terms of the partnerships for the global goals?” and “What does digitalization implicates in terms of supporting long term positive economic, social, and environmental links in the post-COVID-19 era?”
Future of Work Places
Authors: Zachariah Minu , Avanesh Neetha Mary , Arjunan Satya Nandini
Published: July 2022

Hybrids are becoming the order of the day. The word hybrid came into existence to define the offspring of two dissimilar animals. Later, it was used to define plants that picked up the strengths of two varieties and displayed it together. Hybrids were popular in vehicles too. The pandemic that has struck the globe has accentuated the need for a hybrid framework at work. A hybrid work order relates to a flexible system whereby the employees are given the liberty to categorise their workdays between work from home and work from office. It was meant to reinvent traditional workplaces to improve productivity and reduce cost and employee attrition. Most of the organisations do not have the awareness or experience to implement the model. The chapter has examined the development of hybrid workplace models, its role in changing work dynamics, the major issues and challenges relating to its implementation, and a few insights on the best practices in the design and delivery of hybrid models.
Transformational and Authentic Leadership in Telework
Authors: Figueiredo Paula Cristina Nunes , Leal Sandrina Encarnação , Lopes Inês , Cascão A. Ferreira , Gomes Patricia
Published: July 2022

The COVID-19 era has driven virtual work models in the organisational context. Teleworking was the alternative that many organisations found to continue operating. Overnight, many employees started working from home. Leadership practices are essential in times of uncertainty and crisis. This study aims to analyse the perception of teleworking employees regarding the leadership style, specifically the transformational and authentic leaderships. The results show that transformational leadership is predominant in the teleworking context. However, when compared with other studies, teleworking employees perceive less transformational leadership behaviours and more behaviours referring to laissez-faire leadership, as well as the behaviours of transactional leadership. Teleworking employees perceive more behaviours of the authentic leadership style. This study demonstrates the need for leaders to adapt their behaviours to the new working conditions, face-to-face and virtual, to ensure leadership effectiveness.
MATEM
Authors: Jaswal Shivani , Malhotra Manisha
Published: July 2022

The paradigms of Cloud Computing have risen at a very rapid rate. The Cloud Computing demands that a trustworthy or reliable service should be availed by its potential user. However, it is always a challenge for any cloud user to look for service that is suitable as well as reliable in every aspect. For a trustworthy discovery and delivery of cloud services, a multi-layered model i.e., Multi Agent based Trust Evaluation Model (MATEM) has been proposed. It is a multi-agent trust model that will make use of multiple agents to perform and evaluate the credibility of trust through trust evaluation system. Also, the performance validation has proven that the final calculated values of trust will be helpful in providing reliable cloud services to its users.
Reliability-Based Fragility Analysis of RC Frame Buildings Considering Soil-Structure Interaction
Authors: Shiuly Amit , Das Debapriya
Published: July 2022

In the present study, the effect of soil structure interaction (SSI) of low, mid, and high rise (G+1, G+4, and G+9 storey) buildings has been evaluated by nonlinear dynamic analysis using three-dimensional finite element method. Three types of uniform soils, namely hard soil, medium soil, and soft soil, have been considered for the present analysis. These buildings have been subjected to Loma Prieta (1989) earthquake motion and Denali (2002) earthquake motion as near field and far field earthquake motions respectively under the above mentioned soil conditions. From the analysis, the horizontal displacements and percentage of drifts have been determined of all the stories of the buildings under the above mentioned three soil conditions and the two earthquakes. Further, for all the cases, fragility curves have been computed. Furthermore, on the basis of the fragility curve and seismic hazard curve of a region, reliability index (RI) has also been developed.
A Study on the Factors Causing the Intention to Use a Smart Tolling System
Authors: Hur Sung il , Park Yong gi , Jang Jin won
Published: July 2022

Smart tolling, which improved the drawbacks of the existing high-pass system, was developed and built through the Smart Highway R & D project in 2007. To successfully introduce and spread Smart Tolling, it needs to analyze factors that affected by intent to use. This study conducted research based on literature studies and empirical studies and developed a research model to analyze factors causing the users' intention of smart tolling system based on technology acceptance model (TAM) and value-based acceptance model. The main variables of the research model are service characteristics (convenience, reliability), technical characteristics (flexibility, stability), environmental characteristics (switching cost, effectiveness of policy), and intention to use. To test the hypotheses set in this study, frequency analysis, exploratory factor analysis, and confirmatory factor analysis were performed using the SPSS 22.0 program statistical package and AMOSS 18.0. The convenience and reliability presented by service characteristics did not affect the intention to use.