Cyber Harassment Research Articles

To Study on Cyber Crime Burgeoning in India and Crucial Actions Need for Every Cybercrime Victim

India is facing a great deal of challenges due to the rapid digitalization and broad adoption of technology in many different areas. One such concern is cybercrime. In this paper explores the nature, scope, and impact of cybercrime in the Indian context. The rising ubiquity of internet usage has rendered people, companies, and governmental organizations more susceptible to a range of cyber threats, such as identity theft, financial fraud, data breaches, and cyber harassment. Despite developments in cyber security protection, the lack of awareness and poor regulatory frameworks has aggravated the situation. To address these issues, the Indian government has put in place a number of efforts, including the National Cyber Security Policy and the Information Technology Act, 2000. But enforcement is still patchy, and a lot of crimes go unreported or ignored. The problem has been made worse by insufficient regulatory frameworks and a lack of knowledge, even in spite of advances in cyber security measures. But enforcement is still patchy, and a lot of crimes go unreported or ignored. This research paper emphasizes India's cybercrime victims have several legal options, the need for a multimodal strategy that includes improved cyber security infrastructure, better legislative frameworks and greater public awareness in order to tackle cybercrime. In light of the transnational character of cyber threats, it also highlights the significance of international cooperation. In the end, a thorough plan is necessary to protect India's digital environment and guarantee the security and safety of its people in a world that is becoming more interconnected by the day

EU approach towards violence against women and domestic violence – new EU Directive

European Union (EU) approach towards violence against women and domestic violence is analyzed through interconnection with principles of gender equality and nondiscrimination. The combination of gender-based discrimination and gender inequality with other forms of discrimination (economic, political, etc.) very often result in specific forms of violence against women. EU acceded the Istanbul Convention on preventing and combating violence against women and domestic violence of the Council of Europe in June 2023, which was spiritus movens for the adoption of the new EU Directive in this field. Achievements and shortcomings of this Directive are presented, as well as its significance within existing relevant EU primary and secondary legislation. New legislation criminalizes the following offences across the EU: female genital mutilation, forced marriage, non-consensual sharing of intimate images, cyber stalking, cyber harassment and cyber incitement to hatred or violence. However, criminalization of rape is lacking due to the absence of agreement of the constitutional element of sexual consent. Instead, prevention of rape and raising awareness of the importance of central role of consent are included. Taking into account the problem of secondary victimization, the Directive regulates rules on the measures of assistance and protection to victims that are to be secured by Member States, who are obliged to implement Directive in three years period. Directive gains special significance when taking into account relevant official data on violence against women in the EU. This Directive is to be considered the step forward in the direction of realization of gender equality de facto.

The Prevalence of Cyber Harassment among Pre-university Students of Obafemi Awolowo University, Nigeria

The Prevalence of Cyber Harassment among Pre-university Students of Obafemi Awolowo University, Nigeria

Navigating misogynistic cyber harassment: Impacts and challenges faced by Pakistani female journalists

Navigating misogynistic cyber harassment: Impacts and challenges faced by Pakistani female journalists

Cyber Interpersonal Violence: Adolescent Perspectives and Digital Practices.

The pervasive use of technology, especially among adolescents, has enabled cyber communication and brought many advantages but also led to potential violence. The issue of cyber interpersonal violence (CIV) impacting young individuals is increasingly recognized as a matter of public health; however, little is known about adolescents' perspectives of the phenomenon. This study explores adolescents' perspectives on CIV. It seeks to understand their interpretations of abuse, victim impact and reactions, violence escalation, gender issues, victimization and perpetration patterns, and bystander roles. This qualitative study used fifteen focus groups to gather elementary school participants' perspectives on cyber interpersonal violence. From four Portuguese schools, 108 participants (M = 12.87 and SD = 0.31) participated in the study. A thematic analysis uncovered three themes. The results evidenced adolescents' perspectives about CIV. Due to the amount of time spent online, adolescents regularly encounter cyber harassment and recognize the importance of help-seeking. Mental health problems and their influence on the social and educational lives of adolescents is arising as a CIV problem. Parents play a crucial role in mitigating CIV as well as bystanders. Future programs should promote healthy relationships, raise CIV awareness, involve stakeholders, guide parents, integrate perpetrators into programs, and foster effective networking.

Legal Challenges of Cyber Bullying & Online Harassments - A Comparative Analysis

Legal Challenges of Cyber Bullying & Online Harassments - A Comparative Analysis

Ensemble Learning Based Prediction for Cyber Harassment Observations on Tweets

Ensemble Learning Based Prediction for Cyber Harassment Observations on Tweets

Benchmarking Cyber Harassment Dialogue Comprehension through Emotion-Informed Manifestations-Determinants Demarcation

In the digital age, cybercrimes, particularly cyber harassment, have become pressing issues, targeting vulnerable individuals like children, teenagers, and women. Understanding the experiences and needs of the victims is crucial for effective support and intervention. Online conversations between victims and virtual harassment counselors (chatbots) offer valuable insights into cyber harassment manifestations (CHMs) and determinants (CHDs). However, the distinction between CHMs and CHDs remains unclear. This research is the first to introduce concrete definitions for CHMs and CHDs, investigating their distinction through automated methods to enable efficient cyber-harassment dialogue comprehension. We present a novel dataset, Cyber-MaD that contains Cyber harassment dialogues manually annotated with Manifestations and Determinants. Additionally, we design an Emotion-informed Contextual Dual attention Convolution Transformer (E-ConDuCT) framework to extract CHMs and CHDs from cyber harassment dialogues. The framework primarily: a) utilizes inherent emotion features through adjective-noun pairs modeled by an autoencoder, b) employs a unique Contextual Dual attention Convolution Transformer to learn contextual insights; and c) incorporates a demarcation module leveraging task-specific emotional knowledge and a discriminator loss function to differentiate manifestations and determinants. E-ConDuCT outperforms the state-of-the-art systems on the Cyber-MaD corpus, showcasing its potential in the extraction of CHMs and CHDs. Furthermore, its robustness is demonstrated on the emotion cause extraction task using the CARES_CEASE-v2.0 dataset of suicide notes, confirming its efficacy across diverse cause extraction objectives. Access the code and data at 1. https://www.iitp.ac.in/~ai-nlp-ml/resources.html#E-ConDuCT-on-Cyber-MaD, 2. https://github.com/Soumitra816/Manifestations-Determinants.

SOCIAL MEDIA ABUSE AND ITS IMPLICATIONS FOR DEMOCRACY IN NIGERIA

Nigeria’s democracy has been under the siege of incessant crises and these crises are a culmination of the country’s successive years of corruption, human rights violation and in recent times the misuse of social media (through the use of propaganda, cyber bullying and cyber harassment) that heats up the polity and generates bitter politics, hate and bigotry. The implication of this is that it creates a rife environment for continuous electoral violence and ethnic strife that consequently undermines democracy. In the light of this, the objective of this paper seeks to identify how the wrong use of social media can be a threat to the consolidation of democracy in Nigeria. Qualitative method based on document investigation was adopted and the findings from this paper revealed that some of the causes of social media abuse is the culture of gross impunity of the Nigerian society and the lack of effective regulation of social media by governmental institutions. It therefore concludes and recommends that effective policies must be enforced to end the culture of impunity and abuse of social media in order to put an end to ethnic cynicism, ethnic conflicts and hateful politics that breeds sycophants, political violence and the consequent destruction of public administration in Nigeria.

MUTED GROUP THEORY ANOMALIES IN ONLINE GENDER-BASED VIOLENCE EXPERIENCED BY WOMEN JOURNALISTS

Research conducted by PR2Media at the end of 2022 found that 82.6% of 852 female journalists who were study respondents in 34 provinces reported having experienced sexual violence, including Central Java province. However, the research did not specifically discuss KBGO specifically for each region. In fact, digital violence targeting female journalists falls into the category of Online Gender-Based Violence (OGBV), namely acts of violence through internet technology to harass victims. The urgency of this research is to reveal Online Gender-Based Violence experienced by female journalists in Semarang as the capital of Central Java. The purpose of this study is to find out how the experience of OGBV that occurred during their profession, as well as to find out the types of OGBV that have been experienced. This research uses a qualitative method with data collection techniques through in-depth interviews, observations, surveys and literature studies, which are then described descriptively. The findings of this research show that the type of GBV experienced by female journalists in Semarang is cyber harassment (46.7), and the attitude taken by female journalists who are victims of online gender-based violence is to refuse to remain silent, an anomaly of Muted Group Theory

A novel approach to fuzzy N-soft sets and its application for identifying and sanctioning cyber harassment on social media platforms

This study proposes a novel approach to fuzzy N-soft sets for handling cases where membership degree and grade are not related. In the standard model of fuzzy N-soft sets, membership degree and grade are assumed to be directly proportional. This assumption may not hold true in real-world situations, so a more flexible and nuanced approach is necessary. The proposed approach includes two novel algorithms for decision-making problems involving fuzzy N-soft sets. As a result, it is able to be adaptable and sensitive when addressing uncertainties in real-world scenarios, with a particular focus on identifying and sanctioning cyber harassment on social media platforms. Additionally, an innovative perspective and approach to decision-making problems involving fuzzy N-soft sets is introduced by extending an established selection process that prioritizes the dominant parameter, resulting in more precise and dependable outcomes. Our study offers an effective tool for decision-making in various fields, including e-commerce, social media, and product reviews.

Digitalization of Workplace Harassment Against White-Collar Women: An Investigation in Professional Online Platforms

Sexual harassment against women is one of the important social problems addressed all over the world. It is a fact that has existed for hundreds of years, although the place and types of it change. Harassment has been transferred to the digital environment, as everything has become digital with the Internet. It is claimed that women are subjected to harassment while working or looking for a job. To investigate the prevalence of workplace harassment and harassment on online platforms used for professional purposes and its psychological effects on victims, an online nonprobability sampling survey on 245 white-collar women aged 20-40 working in the private sector was conducted. The results suggest that the harassment that women are most exposed to is cyber harassment. It has been observed that 73 women out of every hundred have been subjected to harassment on professional digital platforms. In the types of harassment experienced, persistent online dating requests, receiving unwanted romantic messages, sexual jokes and insults are the most common types of harassment. It has been revealed that the psychological and physiological effects of physical abuse are also seen in victims of cyber harassment.

Cyber Bullying

Cyber bullying or cyber harassment is a form of bullying or harassment using electronic means. Cyber bullying and cyber harassment are also known as online bullying. It has become increasingly common, especially among teenagers and adolescents, due to the communication technology advancements and young people's increased use of such technologies. Cyber bullying is when someone, typically a teenager, bullies or harasses others on the internet and other digital spaces, particularly on social media sites.

Exploring Cyber Harassment among Youth Who Use Social Media

This is an anthropological research which studies cyber harassment on social media among the young people of University of Dhaka. Cyber harassment is an umbrella term and consists several harassing behaviors. There is no concrete definition of it. In general, it is defined as intentional and repeated behavior that is directed to someone through the digital platforms in order to disturb, harm or scare them. Social media is a digital communication platform which is used most by almost all age group around the world. In our country, young people are the main user of social media platforms. So, this study is very relevant in the context of our country to understand cyber harassment. Anthropological methods and its core theoretical tenets which encourage in-depth study of any issue have provided a good framework to this research. This study uses both qualitative and quantitative methods including ten in-depth interviews and a questionnaire based online survey with fifty informants. The present study observes young user’s perception regarding cyber harassment, the nature of cyber harassment from user’s personal experience in social media. Several factors like technical skills, knowledge regarding social media, gender, capital, social network etc. play a great role in shaping their perception. This study also illuminates young people’s understanding of cyber harassment, reasons behind their mild or severe dichotomy of harassment and activities that are considered as cyber harassment by them. This study also explores the nature and extent of cyber harassment from young people’s personal experience on social media. It also observes user’s awareness on personal security through the safety measures they follow to stay safe and the strategies they take after facing cyber harassment on social media. The whole study has been analyzed using Arjun Appadurai’s Technoscapes theory, Pierre Bourdieu’s theory of capital and symbolic violence. This study concludes with a summary of the whole research, some additional opinion of the participants about this research and the role of anthropologists to work in this issue.

Logistic Regression Based Cyber Harassment Identification

Increased online use and allowing users to engage with groups such as digital networking have contributed to the growth of hacking. Online abuse is a new type of harassment that has lately become more prevalent as online communities have grown in popularity. It tends to send messages which included defamatory claims or vocally harassing someone while in the internet group. Only if modern civilization recognizes harassment as it truly is, countless of hidden sufferers may continue to suffer. There have been several studies on cyber bullying, but none of them have been able to offer a solid remedy. By creating a model that can recognize and block bullying-related incoming and outgoing communications, we address this issue in our project. By employing supervised classification techniques on an open source dataset that has been carefully annotated, we hope to provide lexical baselines for this job. We have employed a logistic regression classifier for training and identifying instances of bullying behaviors. The dataset we used is a twitter dataset collected from kaggle. Our model classifies a message whether it’s bullying or not.

Sentiment Analysis of Malaysians Citizen's Emotion towards Cyberbullying in Twitter

Cyberbullying, also known as cyber harassment, is a prevalent issue that significantly impacts the adolescent population in Malaysia. As a form of abusive online behavior, cyberbullying has expanded beyond the physical world into the virtual space, where monitoring activities and changes can be difficult. In 2020, Malaysia ranked second in Asia for cyberbullying among youths due to the widespread use of social media platforms, which have become an ideal breeding ground for negative behavior. This study aims to develop a web-based system that can analyze Malaysian citizens' emotional responses to cyberbullying using machine learning techniques. Additionally, emotional responses gained from Twitter will be characterized using emotional models. The machine learning life-cycle methodology will be implemented in this study. The findings revealed that anger emotion had the highest percentage compared to other emotions such as fear, happiness, love, sadness, and surprise. Expanding the scope of the study to include other social media platforms and demographic groups may provide a more comprehensive understanding of cyberbullying in Malaysia. These recommendations may improve the effectiveness of the web-based system and facilitate the development of more efficient strategies for preventing and mitigating the effects of cyberbullying in Malaysia.

Classification of Virtual Harassment on Social Networks Using Ensemble Learning Techniques

Background: Internet social media platforms have become quite popular, enabling a wide range of online users to stay in touch with their friends and relatives wherever they are at any time. This has led to a significant increase in virtual crime from the inception of these platforms to the present day. Users are harassed online when confidential information about them is stolen, or when another user posts insulting or offensive comments about them. This has posed a significant threat to online social media users, both mentally and psychologically. Methods: This research compares traditional classifiers and ensemble learning in classifying virtual harassment in online social media networks by using both models with four different datasets: seven machine learning algorithms (Nave Bayes NB, Decision Tree DT, K Nearest Neighbor KNN, Logistics Regression LR, Neural Network NN, Quadratic Discriminant Analysis QDA, and Support Vector Machine SVM) and four ensemble learning models (Ada Boosting, Gradient Boosting, Random Forest, and Max Voting). Finally, we compared our results using twelve evaluation metrics, namely: Accuracy, Precision, Recall, F1-measure, Specificity, Matthew’s Correlation Coefficient (MCC), Cohen’s Kappa Coefficient KAPPA, Area Under Curve (AUC), False Discovery Rate (FDR), False Negative Rate (FNR), False Positive Rate (FPR), and Negative Predictive Value (NPV) were used to show the validity of our algorithms. Results: At the end of the experiments, For Dataset 1, Logistics Regression had the highest accuracy of 0.6923 for machine learning algorithms, while Max Voting Ensemble had the highest accuracy of 0.7047. For dataset 2, K-Nearest Neighbor, Support Vector Machine, and Logistics Regression all had the same highest accuracy of 0.8769 in the machine learning algorithm, while Random Forest and Gradient Boosting Ensemble both had the highest accuracy of 0.8779. For dataset 3, the Support Vector Machine had the highest accuracy of 0.9243 for the machine learning algorithms, while the Random Forest ensemble had the highest accuracy of 0.9258. For dataset 4, the Support Vector Machine and Logistics Regression both had 0.8383, while the Max voting ensemble obtained an accuracy of 0.8280. A bar chart was used to represent our results, showing the minimum, maximum, and quartile ranges. Conclusions: Undoubtedly, this technique has assisted in no small measure in comparing the selected machine learning algorithms as well as the ensemble for detecting and exposing various forms of cyber harassment in cyberspace. Finally, the best and weakest algorithms were revealed.

Digital Media Used in Education: The Influence on Cyberbullying Behaviors among Youth Students.

Students, colleagues, and other members of society are increasingly using digital media. Students utilize digital media for a variety of reasons, including communication, gaming, making new friends, and simply being curious. However, there are some disadvantages to using digital media. Cyberbullying, cyberharassment, and cyberstalking are examples of useful digital media activities that can have a negative impact on digital media users and lead to societal issues. Surprisingly, limited studies have investigated cyberbullying in depth, utilizing a broad and varied sample of Middle Eastern institutions. As a result, the purpose of this study is to fill a research vacuum by questioning students' use of digital media for cyber involvement. This research aims to create a model for assessing the ethical consequences of behaviors that directly impact students' psychological health because of their use of digital media. The questionnaire looked at how people used digital media to engage in cyberbullying and cyber engagement, the ethical implications of bullying, and being harassed, stalked, and bullied. The study employed a quantitative questionnaire to collect data to achieve the research goal. It was given to 1012 students who are digital media users. Partial least squares (PLS) and structural equation modeling (SEM) were used to examine the data. Considering the empirical data, nearly half of the participants admitted to being harassed, stalked, or bullied on different digital platforms. The evaluation of discriminant validity is a prerequisite factor for examining possible variables' relationships. The goodness-of-fit index indicates that the model is well-fit. Through the established model, decision-makers and school administration would be able to implement measures that would effectively reduce cyber harassment among students and improve the digital media usage experience.

Cyber harassment of children with special reference to digital games

Cyber harassment of children with special reference to digital games

Dataset: Exploring the Landscape of Cyber Harassment: A Data-driven Approach to Understanding the Legal Framework

This research focuses on the search for articles and literature reviews on cyber harassment. The search was conducted using Lens.org, a reliable indexing agency, by using keywords such as Cyber law and Cyber Harassment. Three keywords were selected and entered into the 'edit search' feature, and the search was filtered by selecting the law category in the subject matter and choosing journal articles as the document type. The data was exported in both CSV and BibTeX formats, and a screenshot was taken of the available data graphs. The goal of this research is to collect data on cyber harassment and its legal implications. The method involved searching scholarly works using specific keywords and filtering the results based on subject matter and document type. The results obtained are valuable as they provide a comprehensive understanding of the current state of cyber harassment and its legal implications.
 Highlights:
 
 Filtering through specific categories and document types is an effective way to obtain relevant literature on cyber harassment.
 The ten articles found provide a diverse range of topics related to cyber harassment, from the impact of technology on online sexual harassment to the legal response to cyberbullying.
 These articles offer valuable insights for future research and can be used as references for scholars studying cyber harassment.