One of these articles comes from the International Journal of Cyber Criminology, the journal of choice to learn how the Internet changes the dynamics of crime, criminals, and criminal organizations-which is, after all, why cybercrime has become a serious and fascinating area of social science research. It has been argued that the issue of online abuse is probably one of the highest-profile areas of our digital output for finding the codification of offline power in the mechanics of technology.

Relationship to Social Sciences Principles

Cyberbullying lends itself quite easily to social sciences theory, whereby the debilitating behaviors can be understood by considering human behavior contextualized within and streamlined by the existential implications of a digital structure. Boundaries that once prohibited violence against others are thus diluted when such behaviors can transcend into a digital context, allowing what might have otherwise been pursued in privacy to instead take place in the public sphere.

This means explanation of human behaviors requires an understanding of the interface between individual-level agency and macro-level phenomena-that is, the structure invariable in sociology. Interventions, by extension, involve the capability of explaining such complex behaviors as a precursor to any meaningful approach to correcting them.

Research Questions and Hypothesis
The article’s primary research questions include:
What are the most prevalent forms of harassment online?

The victims of cyber harassment were beginning to face all sorts of problems: starting from demographic factors such as age, gender, and economic status. A huge point within the hypothesis says that women, together with other targets of discrimination, most especially sexual

minorities or LGBTQ+, experience online harassment more often because there is greater power disparity in society both offline and online.

Research Methods

It is a mixed-methods study combining strengths from quantitative surveys and qualitative interviews. Even though quantitative surveys have their strength in revealing broad- based, easily replicable trends, since they can cover large numbers of respondents, qualitative interviews facilitate the unpacking of certain experiential phenomena beyond the binary levels of frequency and prevalence behind which people are living their lives.

Data and Analysis

In these regards, the quantitative data analysis will be done by using statistical techniques that may indicate the correlations of some demographic variables with gender, race/ethnicity, socio- economic status, types of harassment, and numbers of harassment incidents. Qualitative data through intensive interviewing are analyzed using the method called Thematic Analysis, which summarizes variants of key themes and their modification across interviews.

A combined quantitative-qualitative approach to harassment will thus afford an in-depth insight into the problem in such a way as to paint the picture not only in terms of numbers-that is, ‘how also in terms of experience giving meaning to those numbers: ‘How are people affected?’.

Relation to Course Concepts

This also tangentially relates to class content about the ways that social power is enacted online, especially for those coming from less powerful groups and who are more often in jeopardy compared with their more powerful peers. This will also relate to the idea of social capital and community in promoting resiliency to cyber threats.

Impact on Subordinate Groups

People of color, LGBTQ+, the poor, cis women, people with disabilities, and anyone not male- identified are highly vulnerable because of their experiences with online harassment. The plethora of these experiences exacerbates existing inequalities, pushing many into unsustainable levels of stress and exclusion. It is here that perhaps Haidle’s discussion of such groups creates the most significant turn in discussing technology’s role in the perpetuation of lived inequalities.

Social Contributions

In other words, this study impressively fulfills the purpose of societal relevance by extending our knowledge about online harassment. This contribution will first let policymakers, educators, and advocates know what kind of online abuse is especially problematic to vulnerable groups. It allows for targeted interventions that can grant more support.

In conclusion

The contribution of this study to a safe online environment lies in its dealing with one of the causes of cyber harassment. Framing cyber harassment in the context of a social science, added to the characteristic of online behavior being human, serves to underline additional work yet to be accomplished in terms of protecting vulnerable communities and inducing the right kind of stigma in the digital era. Without studies like this, there simply will not be a movement toward an equitable future.

Article Review #2: Understanding the Use of Artificial Intelligence in Cybercrime

Name: [Al-Sadiq Azeez] Date:[11/17/24]

Introduction
The article “Understanding the Use of Artificial Intelligence in Cybercrime” explores how criminals are using artificial intelligence (AI) for cybercrimes. Published in the *International Journal of Cybersecurity Intelligence & Cybercrime, the article explains how AI is being misused for creating fake videos (deepfakes) and tricking people into sharing their personal information (social engineering). This review will summarize the main points of the article, including its research questions, methods, and its connection to social science.

Topic and Social Science Principles
The topic of AI in cybercrime is linked to social science fields like criminology and sociology. The article shows how criminals are using AI, a technology originally designed for good, for illegal activities. This is related to the concept of deviance, where certain behaviors break social norms, and social control, which is how society tries to stop crime. The use of AI for crime represents a new type of deviant behavior, which requires new ways of controlling crime.

Research Questions or Hypotheses
The article suggests several key questions:
1. How are criminals using AI to carry out more complex cybercrimes, such as identity theft and phishing?
2. What are the ethical, legal, and social issues surrounding the use of AI in crime?
3. How can law enforcement and cybersecurity experts stop AI-related cybercrimes?

These questions help us understand the risks of AI and how society needs to respond to these new types of crimes.

Research Methods
The study uses a qualitative method, meaning the authors analyze case studies and articles about AI-driven cybercrime. They look at different examples of AI used in crime, such as deepfakes and AI- enhanced social engineering attacks, and analyze expert opinions. This method helps explain how AI is both beneficial and harmful.

Data and Analysis
The article explains various types of AI-related cybercrimes. Descriptive analysis is used to categorize crimes like deepfakes, where criminals create fake videos to deceive people. The article also discusses AI-driven phishing, where criminals use AI to make fake emails appear more real. The researchers identify patterns in these crimes and explain how AI makes them more difficult to stop.

Concepts from PowerPoint Presentations
The article connects to class concepts like deviance and social control. AI-driven crimes are a new form of deviant behavior, as criminals are using technology to break the law. The article also touches on social control because traditional methods of preventing crime are not enough to stop these new AI-based crimes. This connects to what we learned about how society struggles to keep up with new types of crime.

Marginalized Groups
While the article does not focus specifically on marginalized groups, it highlights that they are often more affected by AI-driven crimes. For example, deepfake technology can be used to target women or people from minority groups, damaging their reputations. AI-based social engineering attacks often affect people who are less familiar with technology, such as older adults or those with lower income, making them more vulnerable to scams.

Contributions to Society
The article contributes by raising awareness about the risks of AI in cybercrime. It calls for stronger cybersecurity laws and better education to protect people from AI-driven crimes. The authors also suggest that governments and private companies should work together to stop AI misuse. By understanding how AI is being used in crime, society can take steps to protect itself.

Conclusion
In conclusion, the article “Understanding the Use of Artificial Intelligence in Cybercrime” highlights how AI is being misused by criminals and the challenges this creates for law enforcement and society. It calls for new policies and better cooperation between companies and governments to prevent AI-related cybercrimes. The research provides important insights into how AI is changing the way crimes are committed and how society can respond.

**References**
Choi, S., Dearden, T., & Parti, K. (2024). Understanding the use of artificial intelligence in cybercrime. *International Journal of Cybersecurity Intelligence & Cybercrime, 7*(2), – . https://doi.org/10.52306/2578-3289.1185
Available at: https://vc.bridgew.edu/ijcic/vol7/iss2/1