Download or read book Predicting Cyberbullying written by Christopher Paul Barlett and published by Academic Press. This book was released on 2019-04-06 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predicting Cyberbullying: Research, Theory, and Intervention delves into the theoretical advances that have been made to predict cyberbullying perpetration. It examines myriad psychological- and communication-based theories, discusses the relevant research to support (or not) each theory, and elucidates the strengths and limitations of these theories. Moreover, the book differentiates cyberbullying from traditional bullying to expand on a theory that takes such differences into account to predict perpetration. In addition, it adapts interventions to address these nuanced theoretical advancements and concludes with an examination of validated psychological theories that can inform interventions and reduce cyberbullying. The book is an effective and concise reference for psychologists, school administrators, counselors and psychological researchers looking to understand theory and interventions for cyberbullies. Focuses on the cyberbully perpetrator Balances theory with interventional applications Identifies key risk factors in those who cyberbully Explores the scope of theoretically driven hypotheses specific to cyberbullying
Download or read book Handbook of Research on Cyberbullying and Online Harassment in the Workplace written by Ramos Salazar, Leslie and published by IGI Global. This book was released on 2020-10-23 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: Given users’ heavy reliance of modern communication technologies such as mobile and tablet devices, laptops, computers, and social media networks, workplace cyberbullying and online harassment have become escalating problems around the world. Organizations of all sizes and sectors (public and private) may encounter workplace cyberbullying within and outside the boundaries of physical offices. Workplace cyberbullying affects the entire company, as victims suffer from psychological trauma and mental health issues that can lead to anxiety and depression, which, in turn, can cause absenteeism, job turnover, and retaliation. Thus, businesses must develop effective strategies to prevent and resolve such issues from becoming too large to manage. The Handbook of Research on Cyberbullying and Online Harassment in the Workplace provides in-depth research that explores the theoretical and practical measures of managing bullying behaviors within an organization as well as the intervention strategies that should be employed. The book takes a look at bullying behavior across a variety of industries, including government and educational institutions, and examines social and legislative issues, policies and legal cases, the impact of online harassment and disruption of business processes and organizational culture, and prevention techniques. Featuring coverage on a broad range of topics such as sexual abuse and trolling, this book is ideally designed for business managers and executives, human resource managers, practitioners, policymakers, academicians, researchers, and students.
Download or read book Cyberbullying in the Global Playground written by Qing Li and published by John Wiley & Sons. This book was released on 2012-02-20 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cyberbullying in the Global Playground provides the first global, in-depth analysis of the emerging phenomenon of cyberbullying. Offers the first thorough comparative account of recent research into the emerging global phenomenon of cyberbullying Provides an international perspective on the prevalence and nature of cyberbullying Presents recent authoritative research within a critical perspective, drawing out theoretical and practical implications for policy and practice May be used to help design intervention, evaluation, and policy strategies for effective efforts to combat the international phenomenon of cyberbullying
Download or read book 5 FIVE DATA SCIENCE PROJECTS FOR ANALYSIS CLASSIFICATION PREDICTION AND SENTIMENT ANALYSIS WITH PYTHON GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2022-04-29 with total page 979 pages. Available in PDF, EPUB and Kindle. Book excerpt: PROJECT 1: SUPERMARKET SALES ANALYSIS AND PREDICTION USING MACHINE LEARNING WITH PYTHON GUI The dataset used in this project consists of the growth of supermarkets with high market competitions in most populated cities. The dataset is one of the historical sales of supermarket company which has recorded in 3 different branches for 3 months data. Predictive data analytics methods are easy to apply with this dataset. Attribute information in the dataset are as follows: Invoice id: Computer generated sales slip invoice identification number; Branch: Branch of supercenter (3 branches are available identified by A, B and C); City: Location of supercenters; Customer type: Type of customers, recorded by Members for customers using member card and Normal for without member card; Gender: Gender type of customer; Product line: General item categorization groups - Electronic accessories, Fashion accessories, Food and beverages, Health and beauty, Home and lifestyle, Sports and travel; Unit price: Price of each product in $; Quantity: Number of products purchased by customer; Tax: 5% tax fee for customer buying; Total: Total price including tax; Date: Date of purchase (Record available from January 2019 to March 2019); Time: Purchase time (10am to 9pm); Payment: Payment used by customer for purchase (3 methods are available – Cash, Credit card and Ewallet); COGS: Cost of goods sold; Gross margin percentage: Gross margin percentage; Gross income: Gross income; and Rating: Customer stratification rating on their overall shopping experience (On a scale of 1 to 10). In this project, you will perform predicting rating using machine learning. The machine learning models used in this project to predict clusters as target variable are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, LGBM, Gradient Boosting, XGB, and MLP. Finally, you will plot boundary decision, distribution of features, feature importance, cross validation score, and predicted values versus true values, confusion matrix, learning curve, performance of the model, scalability of the model, training loss, and training accuracy. PROJECT 2: DETECTING CYBERBULLYING TWEETS USING MACHINE LEARNING AND DEEP LEARNING WITH PYTHON GUI As social media usage becomes increasingly prevalent in every age group, a vast majority of citizens rely on this essential medium for day-to-day communication. Social media’s ubiquity means that cyberbullying can effectively impact anyone at any time or anywhere, and the relative anonymity of the internet makes such personal attacks more difficult to stop than traditional bullying. On April 15th, 2020, UNICEF issued a warning in response to the increased risk of cyberbullying during the COVID-19 pandemic due to widespread school closures, increased screen time, and decreased face-to-face social interaction. The statistics of cyberbullying are outright alarming: 36.5% of middle and high school students have felt cyberbullied and 87% have observed cyberbullying, with effects ranging from decreased academic performance to depression to suicidal thoughts. In light of all of this, this dataset contains more than 47000 tweets labelled according to the class of cyberbullying: Age; Ethnicity; Gender; Religion; Other type of cyberbullying; and Not cyberbullying. The data has been balanced in order to contain ~8000 of each class. The models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, Adaboost, LGBM classifier, Gradient Boosting, XGB classifier, LSTM, and CNN. Three feature scaling used in machine learning are raw, minmax scaler, and standard scaler. Finally, you will develop a GUI using PyQt5 to plot cross validation score, predicted values versus true values, confusion matrix, learning curve, decision boundaries, performance of the model, scalability of the model, training loss, and training accuracy. PROJECT 3: HIGHER EDUCATION STUDENT ACADEMIC PERFORMANCE ANALYSIS AND PREDICTION USING MACHINE LEARNING WITH PYTHON GUI The dataset used in this project was collected from the Faculty of Engineering and Faculty of Educational Sciences students in 2019. The purpose is to predict students' end-of-term performances using ML techniques. Attribute information in the dataset are as follows: Student ID; Student Age (1: 18-21, 2: 22-25, 3: above 26); Sex (1: female, 2: male); Graduated high-school type: (1: private, 2: state, 3: other); Scholarship type: (1: None, 2: 25%, 3: 50%, 4: 75%, 5: Full); Additional work: (1: Yes, 2: No); Regular artistic or sports activity: (1: Yes, 2: No); Do you have a partner: (1: Yes, 2: No); Total salary if available (1: USD 135-200, 2: USD 201-270, 3: USD 271-340, 4: USD 341-410, 5: above 410); Transportation to the university: (1: Bus, 2: Private car/taxi, 3: bicycle, 4: Other); Accommodation type in Cyprus: (1: rental, 2: dormitory, 3: with family, 4: Other); Mother's education: (1: primary school, 2: secondary school, 3: high school, 4: university, 5: MSc., 6: Ph.D.); Father's education: (1: primary school, 2: secondary school, 3: high school, 4: university, 5: MSc., 6: Ph.D.); Number of sisters/brothers (if available): (1: 1, 2:, 2, 3: 3, 4: 4, 5: 5 or above); Parental status: (1: married, 2: divorced, 3: died - one of them or both); Mother's occupation: (1: retired, 2: housewife, 3: government officer, 4: private sector employee, 5: self-employment, 6: other); Father's occupation: (1: retired, 2: government officer, 3: private sector employee, 4: self-employment, 5: other); Weekly study hours: (1: None, 2: <5 hours, 3: 6-10 hours, 4: 11-20 hours, 5: more than 20 hours); Reading frequency (non-scientific books/journals): (1: None, 2: Sometimes, 3: Often); Reading frequency (scientific books/journals): (1: None, 2: Sometimes, 3: Often); Attendance to the seminars/conferences related to the department: (1: Yes, 2: No); Impact of your projects/activities on your success: (1: positive, 2: negative, 3: neutral); Attendance to classes (1: always, 2: sometimes, 3: never); Preparation to midterm exams 1: (1: alone, 2: with friends, 3: not applicable); Preparation to midterm exams 2: (1: closest date to the exam, 2: regularly during the semester, 3: never); Taking notes in classes: (1: never, 2: sometimes, 3: always); Listening in classes: (1: never, 2: sometimes, 3: always); Discussion improves my interest and success in the course: (1: never, 2: sometimes, 3: always); Flip-classroom: (1: not useful, 2: useful, 3: not applicable); Cumulative grade point average in the last semester (/4.00): (1: <2.00, 2: 2.00-2.49, 3: 2.50-2.99, 4: 3.00-3.49, 5: above 3.49); Expected Cumulative grade point average in the graduation (/4.00): (1: <2.00, 2: 2.00-2.49, 3: 2.50-2.99, 4: 3.00-3.49, 5: above 3.49); Course ID; and OUTPUT: Grade (0: Fail, 1: DD, 2: DC, 3: CC, 4: CB, 5: BB, 6: BA, 7: AA). The models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, Adaboost, LGBM classifier, Gradient Boosting, and XGB classifier. Three feature scaling used in machine learning are raw, minmax scaler, and standard scaler. Finally, you will develop a GUI using PyQt5 to plot cross validation score, predicted values versus true values, confusion matrix, learning curve, decision boundaries, performance of the model, scalability of the model, training loss, and training accuracy. PROJECT 4: COMPANY BANKRUPTCY ANALYSIS AND PREDICTION USING MACHINE LEARNING WITH PYTHON GUI The dataset was collected from the Taiwan Economic Journal for the years 1999 to 2009. Company bankruptcy was defined based on the business regulations of the Taiwan Stock Exchange. Attribute information in the dataset are as follows: Y - Bankrupt?: Class label; X1 - ROA(C) before interest and depreciation before interest: Return On Total Assets(C); X2 - ROA(A) before interest and % after tax: Return On Total Assets(A); X3 - ROA(B) before interest and depreciation after tax: Return On Total Assets(B); X4 - Operating Gross Margin: Gross Profit/Net Sales; X5 - Realized Sales Gross Margin: Realized Gross Profit/Net Sales; X6 - Operating Profit Rate: Operating Income/Net Sales; X7 - Pre-tax net Interest Rate: Pre-Tax Income/Net Sales; X8 - After-tax net Interest Rate: Net Income/Net Sales; X9 - Non-industry income and expenditure/revenue: Net Non-operating Income Ratio; X10 - Continuous interest rate (after tax): Net Income-Exclude Disposal Gain or Loss/Net Sales; X11 - Operating Expense Rate: Operating Expenses/Net Sales; X12 - Research and development expense rate: (Research and Development Expenses)/Net Sales X13 - Cash flow rate: Cash Flow from Operating/Current Liabilities; X14 - Interest-bearing debt interest rate: Interest-bearing Debt/Equity; X15 - Tax rate (A): Effective Tax Rate; X16 - Net Value Per Share (B): Book Value Per Share(B); X17 - Net Value Per Share (A): Book Value Per Share(A); X18 - Net Value Per Share (C): Book Value Per Share(C); X19 - Persistent EPS in the Last Four Seasons: EPS-Net Income; X20 - Cash Flow Per Share; X21 - Revenue Per Share (Yuan ¥): Sales Per Share; X22 - Operating Profit Per Share (Yuan ¥): Operating Income Per Share; X23 - Per Share Net profit before tax (Yuan ¥): Pretax Income Per Share; X24 - Realized Sales Gross Profit Growth Rate; X25 - Operating Profit Growth Rate: Operating Income Growth; X26 - After-tax Net Profit Growth Rate: Net Income Growth; X27 - Regular Net Profit Growth Rate: Continuing Operating Income after Tax Growth; X28 - Continuous Net Profit Growth Rate: Net Income-Excluding Disposal Gain or Loss Growth; X29 - Total Asset Growth Rate: Total Asset Growth; X30 - Net Value Growth Rate: Total Equity Growth; X31 - Total Asset Return Growth Rate Ratio: Return on Total Asset Growth; X32 - Cash Reinvestment %: Cash Reinvestment Ratio X33 - Current Ratio; X34 - Quick Ratio: Acid Test; X35 - Interest Expense Ratio: Interest Expenses/Total Revenue; X36 - Total debt/Total net worth: Total Liability/Equity Ratio; X37 - Debt ratio %: Liability/Total Assets; X38 - Net worth/Assets: Equity/Total Assets; X39 - Long-term fund suitability ratio (A): (Long-term Liability+Equity)/Fixed Assets; X40 - Borrowing dependency: Cost of Interest-bearing Debt; X41 - Contingent liabilities/Net worth: Contingent Liability/Equity; X42 - Operating profit/Paid-in capital: Operating Income/Capital; X43 - Net profit before tax/Paid-in capital: Pretax Income/Capital; X44 - Inventory and accounts receivable/Net value: (Inventory+Accounts Receivables)/Equity; X45 - Total Asset Turnover; X46 - Accounts Receivable Turnover; X47 - Average Collection Days: Days Receivable Outstanding; X48 - Inventory Turnover Rate (times); X49 - Fixed Assets Turnover Frequency; X50 - Net Worth Turnover Rate (times): Equity Turnover; X51 - Revenue per person: Sales Per Employee; X52 - Operating profit per person: Operation Income Per Employee; X53 - Allocation rate per person: Fixed Assets Per Employee; X54 - Working Capital to Total Assets; X55 - Quick Assets/Total Assets; X56 - Current Assets/Total Assets; X57 - Cash/Total Assets; X58 - Quick Assets/Current Liability; X59 - Cash/Current Liability; X60 - Current Liability to Assets; X61 - Operating Funds to Liability; X62 - Inventory/Working Capital; X63 - Inventory/Current Liability X64 - Current Liabilities/Liability; X65 - Working Capital/Equity; X66 - Current Liabilities/Equity; X67 - Long-term Liability to Current Assets; X68 - Retained Earnings to Total Assets; X69 - Total income/Total expense; X70 - Total expense/Assets; X71 - Current Asset Turnover Rate: Current Assets to Sales; X72 - Quick Asset Turnover Rate: Quick Assets to Sales; X73 - Working capitcal Turnover Rate: Working Capital to Sales; X74 - Cash Turnover Rate: Cash to Sales; X75 - Cash Flow to Sales; X76 - Fixed Assets to Assets; X77 - Current Liability to Liability; X78 - Current Liability to Equity; X79 - Equity to Long-term Liability; X80 - Cash Flow to Total Assets; X81 - Cash Flow to Liability; X82 - CFO to Assets; X83 - Cash Flow to Equity; X84 - Current Liability to Current Assets; X85 - Liability-Assets Flag: 1 if Total Liability exceeds Total Assets, 0 otherwise; X86 - Net Income to Total Assets; X87 - Total assets to GNP price; X88 - No-credit Interval; X89 - Gross Profit to Sales; X90 - Net Income to Stockholder's Equity; X91 - Liability to Equity; X92 - Degree of Financial Leverage (DFL); X93 - Interest Coverage Ratio (Interest expense to EBIT); X94 - Net Income Flag: 1 if Net Income is Negative for the last two years, 0 otherwise; and X95 - Equity to Liabilitys. The models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, Adaboost, LGBM classifier, Gradient Boosting, and XGB classifier. Three feature scaling used in machine learning are raw, minmax scaler, and standard scaler. Finally, you will develop a GUI using PyQt5 to plot cross validation score, predicted values versus true values, confusion matrix, learning curve, decision boundaries, performance of the model, scalability of the model, training loss, and training accuracy. PROJECT 5: DATA SCIENCE FOR RAIN CLASSIFICATION AND PREDICTION WITH PYTHON GUI This dataset contains about 10 years of daily weather observations from many locations across Australia. RainTomorrow is the target variable to predict. You will determine rain or not in the next day. This column is Yes if the rain for that day was 1mm or more. Observations were drawn from numerous weather stations. The daily observations are available from http://www.bom.gov.au/climate/data. The dataset contains 23 attributes. Some of them are as follows: About some of them are: DATE - The date of observation; LOCATION - The common name of the location of the weather station; MINTEMP - The minimum temperature in degrees celsius; MAXTEMP - The maximum temperature in degrees celsius; RAINFALL - The amount of rainfall recorded for the day in mm; EVAPORATION - The so-called Class A pan evaporation (mm) in the 24 hours to 9am; SUNSHINE - The number of hours of bright sunshine in the day; WINDGUESTDIR - The direction of the strongest wind gust in the 24 hours to midnight; WINDGUESTSPEED- The speed (km/h) of the strongest wind gust in the 24 hours to midnight; and WINDDIR9AM - Direction of the wind at 9am. The models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, Adaboost, LGBM classifier, Gradient Boosting, and XGB classifier. Three feature scaling used in machine learning are raw, minmax scaler, and standard scaler. Finally, you will develop a GUI using PyQt5 to plot cross validation score, predicted values versus true values, confusion matrix, learning curve, decision boundaries, performance of the model, scalability of the model, training loss, and training accuracy.
Download or read book Cyberbullying and Online Harms written by Helen Cowie and published by Taylor & Francis. This book was released on 2023-05-02 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cyberbullying and Online Harms identifies online harms and their impact on young people, from communities to campuses, exploring current and future interventions to reduce and prevent online harassment and aggression. This important resource brings together eminent international researchers whose work shines a light on social issues such as bullying/cyberbullying, racism, homophobia, hate crime, and social exclusion. The text collates into one volume current knowledge and evidence of cyberbullying and its effect on young people, facilitating action to protect victims, challenge perpetrators and develop policies and practices to change cultures that are discriminatory and divisive. It also provides a space where those who have suffered online harms and who have often been silenced in the past may have a voice in telling their experiences and recounting interventions and policies that helped them to create safer spaces in which to live in their community, study in their educational institutions and socialise with their peer group. This is essential reading for researchers, academics, undergraduates and postgraduates in sociology, psychology, criminology, media and communication studies, as well as practitioners and policymakers in psychology, education, sociology, criminology, psychiatry, counselling and psychotherapy, and anyone concerned with the issue of bullying, cyberbullying and online harms among young people in higher education.
Download or read book Research Anthology on Combating Cyber Aggression and Online Negativity written by Management Association, Information Resources and published by IGI Global. This book was released on 2022-03-04 with total page 1658 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advent of the internet and social media were landmarks in furthering communication technologies. Through social media websites, families, friends, and communities could connect in a way never seen. Though these websites are helpful tools in facilitating positive interaction, they have also allowed users to verbally attack and bully each other with no fear of repercussion. Moreover, online predators will often use these tools to harass, stalk, and in some cases even lure their victims. Particularly rampant among adolescents, these harmful actions must be mitigated in order to safeguard the mental health and physical safety of users. The Research Anthology on Combating Cyber-Aggression and Online Negativity discusses the research behind cyber-aggression and cyber bullying, as well as methods to predict and prevent online negativity. It presents policy, technological, and human intervention practices against cyber-aggression. Covering topics such as media literacy, demographic variables, and workplace cyberbullying, this major reference work is a critical resource for students and educators of higher education, libraries, social media administrators, government organizations, K-12 teachers, computer scientists, sociologists, psychologists, human resource managers, researchers, and academicians.
Download or read book Child and Adolescent Online Risk Exposure written by Michelle F. Wright and published by Academic Press. This book was released on 2020-11-19 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Child and Adolescent Online Risk Exposure: An Ecological Perspective focuses on online risks and outcomes for children and adolescents using an ecological perspective (i.e., the intersection of individuals in relevant contexts) for a better understanding of risks associated with the youth online experience. The book examines the specific consequences of online risks for youth and demonstrates how to develop effective and sensitive interventions and policies. Sections discuss why online risks are important, individual and contextual factors, different types of risk, online risks among special populations, such as LGBT youth, physically or intellectually disabled youth, and ethnic and religious minorities, and intervention efforts. Examines online risks such as problematic internet use, contact risk behaviors, online exploitation, online hate, cyberbullying, and cyberstalking Explores the concept of digital citizenship Includes theoretical considerations and the prevalence of online risks Covers policy and intervention recommendations for reducing online risks
Download or read book Cyber Criminology written by Hamid Jahankhani and published by Springer. This book was released on 2018-11-27 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the current and emerging challenges of cyber criminology, victimization and profiling. It is a compilation of the outcomes of the collaboration between researchers and practitioners in the cyber criminology field, IT law and security field. As Governments, corporations, security firms, and individuals look to tomorrow’s cyber security challenges, this book provides a reference point for experts and forward-thinking analysts at a time when the debate over how we plan for the cyber-security of the future has become a major concern. Many criminological perspectives define crime in terms of social, cultural and material characteristics, and view crimes as taking place at a specific geographic location. This definition has allowed crime to be characterised, and crime prevention, mapping and measurement methods to be tailored to specific target audiences. However, this characterisation cannot be carried over to cybercrime, because the environment in which such crime is committed cannot be pinpointed to a geographical location, or distinctive social or cultural groups. Due to the rapid changes in technology, cyber criminals’ behaviour has become dynamic, making it necessary to reclassify the typology being currently used. Essentially, cyber criminals’ behaviour is evolving over time as they learn from their actions and others’ experiences, and enhance their skills. The offender signature, which is a repetitive ritualistic behaviour that offenders often display at the crime scene, provides law enforcement agencies an appropriate profiling tool and offers investigators the opportunity to understand the motivations that perpetrate such crimes. This has helped researchers classify the type of perpetrator being sought. This book offers readers insights into the psychology of cyber criminals, and understanding and analysing their motives and the methodologies they adopt. With an understanding of these motives, researchers, governments and practitioners can take effective measures to tackle cybercrime and reduce victimization.
Download or read book MSEA 2023 written by Gaikar Vilas and published by European Alliance for Innovation. This book was released on 2023-07-21 with total page 859 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 2nd International Conference on Mathematical Statistics and Economic Analysis (MSEA 2023) was held virtually from 26-28 May 2023 in Nanjing, China. The conference was attended by researchers, teachers, students and engineers in the field of mathematical statistics and economic analysis. Through data statistics and analysis, we can quickly understand the pattern of economic development. This conference combines mathematical statistics and economic analysis, explores the relationship between the two, and provides a platform for experts and scholars in the fields of mathematical statistics and economic analysis to discuss related issues and exchange ideas. Therefore, we hope to create a forum for sharing research results and exploring future research directions, so that participants can learn about the latest research directions, contents and results of mathematical statistics and economic analysis; secondly, we hope that the conference can provide solutions to the major problems facing mathematical statistics and economic analysis, and create a space that encourages discussion and joint development of research, technological development and innovation.
Download or read book Cyberbullying and Values Education written by Angel Nga Man Leung and published by Taylor & Francis. This book was released on 2023-11-10 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by scholars from both the Western and Chinese contexts, this monograph discusses the relation between cyberbullying and socio-emotional-moral competencies, feasible interventions by integrating values education, and provides future directions in the field of cyberpsychology. Cyberbullying has become a growing concern in the digital age as it brings devastating impacts on its victims. Educating the younger generation, particularly through values education, also known as character, moral, or social-emotional learning, helps equip children and adolescents with the necessary ethical and moral attitudes, and foster the necessary socio-emotional competencies for them to navigate the digital world as responsible cyber-citizens. A central focus of the book is intervention and education. Cultivating competences and responsible use of technology in the younger generation through values education and evidence-based intervention helps combat cyberbullying. Families, schools, and communities can work together with suitable school programs, teacher education, and parents/school collaboration to help students cope with cyberbullying and create safer online spaces for them. Technology itself is not inherently good or bad but shaped by human choices and values. Supported by empirical evidence and theoretical insights, this book suggests ways to promote moral and emotional skills, foster digital citizenship, and encourage ethical technology design. This book provides a comprehensive understanding of cyberbullying. This timely resource will contribute to creating a safer and more positive online environment for all. It will inform researchers, educators, parents, and the community in combating cyberbullying by enabling children and adolescents to be responsible, ethical, and happy netizens.
Download or read book Cyberbullying written by Lucy R. Betts and published by Springer. This book was released on 2016-08-12 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing on research evidence and media coverage, this book explores a number of key debates surrounding cyberbullying. The increasing digitization of society affords many benefits; however, some of these benefits are offset by more adverse consequences. Cyberbullying represents one of the adverse consequences of technology use, which has become a topic of increasing societal concern. Betts adopts a critical stance to exploring issues around the definition of cyberbullying, the unique nature of cyberbullying compared to other forms of bullying, the variation in the reported prevalence rates of cyberbullying, the consequences of involvement in cyberbullying, and the steps that can be taken to tackle cyberbullying.
Download or read book Data Communication and Networks written by Lakhmi C. Jain and published by Springer Nature. This book was released on 2019-10-25 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected high-quality papers presented at the International Conference on Computing, Power and Communication Technologies 2019 (GUCON 2019), organized by Galgotias University, India, in September 2019. The content is divided into three sections – data mining and big data analysis, communication technologies, and cloud computing and computer networks. In-depth discussions of various issues within these broad areas provide an intriguing and insightful reference guide for researchers, engineers and students alike.
Download or read book International Perspectives on Cyberbullying written by Anna Costanza Baldry and published by Springer. This book was released on 2018-05-08 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together an international group of experts to present the latest psychosocial and developmental criminological research on cyberbullying, cybervictimization and intervention. With contributions from a wide range of European countries, including Cyprus, Greece, Ireland, Italy, France, Hungary, Spain, and the United Kingdom, as well as from Canada and the USA, this authoritative volume explores the nature, risk factors, and prevalence of cyberbullying among children and adolescents. A particularly original focus is directed towards the Tabby project (Threat Assessment of online Bullying Behaviour among Youngsters), an intervention programme based on the threat and risk assessment approach which seeks to prevent the occurrence of violence and its recidivism. Presenting cutting-edge research on developmental criminology and legal psychology, International Perspectives on Cyberbullying is a comprehensive resource for practitioners, teachers, parents, and researchers, as well as scholars of criminology, psychology, and education.
Download or read book Family Bullying and Cyberbullying written by Raul Navarro Olivas and published by MDPI. This book was released on 2019-06-24 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite the significant decrease in bullying that has been reported in many countries during the last two decades, bullying continues to be a significant problem among young people. Given the increase of internet use among youth, researchers have started to pay attention to cyberspace, understanding that it may be a fertile ground for bullying behaviors, specifically, what is known as cyberbullying. “Family, Bullying and Cyberbullying” examines the association of several family variables with bullying in offline and online environments during childhood and adolescence. Contributors from the Americas, Canada, Asia, and Europe offer cutting-edge research on family dynamics, bystander behaviors, parents’ and educators’ perceptions, and bullying and cyberbullying prevention and intervention strategies of bullying for school and home. This book also provides an analysis of the current research on the influence of family in the electronic bullying. Research topics included in the book: 1) Parental education and bullying and cyberbullying; 2) Parental monitoring and cyberbullying; 3) Parental communication and feelings of affiliation; 4) Student and educator perspective on cyberbullying; 5) Parents’ responses to bullying; 6) Parental mediation and bystander behaviors; 7) Development of scales to measure cyberbullying and high internet risks. “Family, Bullying and Cyberbullying” is an essential resource for researchers, graduate students, families, and practitioners in social education, social work, teacher education, and psychology.
Download or read book Predicted Humans written by Simona Chiodo and published by Taylor & Francis. This book was released on 2024-06-14 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predicting our future as individuals is central to the role of much emerging technology, from hiring algorithms that predict our professional success (or failure) to biomarkers that predict how long (or short) our healthy (or unhealthy) life will be. Yet, much in Western culture, from scripture to mythology to philosophy, suggests that knowing one’s future may not be in the subject’s best interests and might even lead to disaster. If predicting our future as individuals can be harmful as well as beneficial, why are we so willing to engage in so much prediction, from cradle to grave? This book offers a philosophical answer, reflecting on seminal texts in Western culture to argue that predicting our future renders much of our existence the automated effect of various causes, which, in turn, helps to alleviate the existential burden of autonomously making sense of our lives in a more competitive, demanding, accelerated society. An exploration of our tendency in a technological era to engineer and so rid ourselves of that which has hitherto been our primary reason for being – making life plans for a successful future, while faced with epistemological and ethical uncertainties – Predicted Humans will appeal to scholars of philosophy and social theory with interests in questions of moral responsibility and meaning in an increasingly technological world.
Download or read book Data Analytics for the Social Sciences written by G. David Garson and published by Routledge. This book was released on 2021-11-30 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics for the Social Sciences is an introductory, graduate-level treatment of data analytics for social science. It features applications in the R language, arguably the fastest growing and leading statistical tool for researchers. The book starts with an ethics chapter on the uses and potential abuses of data analytics. Chapters 2 and 3 show how to implement a broad range of statistical procedures in R. Chapters 4 and 5 deal with regression and classification trees and with random forests. Chapter 6 deals with machine learning models and the "caret" package, which makes available to the researcher hundreds of models. Chapter 7 deals with neural network analysis, and Chapter 8 deals with network analysis and visualization of network data. A final chapter treats text analysis, including web scraping, comparative word frequency tables, word clouds, word maps, sentiment analysis, topic analysis, and more. All empirical chapters have two "Quick Start" exercises designed to allow quick immersion in chapter topics, followed by "In Depth" coverage. Data are available for all examples and runnable R code is provided in a "Command Summary". An appendix provides an extended tutorial on R and RStudio. Almost 30 online supplements provide information for the complete book, "books within the book" on a variety of topics, such as agent-based modeling. Rather than focusing on equations, derivations, and proofs, this book emphasizes hands-on obtaining of output for various social science models and how to interpret the output. It is suitable for all advanced level undergraduate and graduate students learning statistical data analysis.
Download or read book Interventions to Reduce Bullying and Cyberbullying written by Peter K. Smith and published by MDPI. This book was released on 2019-08-02 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue Interventions to Reduce Bullying and Cyberbullying that was published in IJERPH