Descriptions:
In recent years, with explosive growth in E-commerce, most business activities have transformed from traditional to Web platforms. The need emerged to utilize the electronic shopping system so consumers and users could browse the items and know the users' thoughts about them to make a purchase, request a service, or visit a location based on the information on those Web platforms. A User or Customer Review is the expression of an opinion, experience, or recommendation on a particular product or item. However, these opinions play a crucial part in others' decision-making. Therefore, they may be beneficial to the success of any organization.
The characteristics of internet marketing and shopping Websites opened up avenues for people to buy, sell, and express views on any goods (such as a mobile phone, laptop, or automobile, etc) or use such services ( such as restaurants, hotels, bookstore, airline ticket, etc). Users share their expertise on these websites by rating, reviewing, commenting, suggesting, or recommending. To provide just a few examples, a person's choice to buy a vehicle or laptop, rent a hotel room, go to another country, and so on will be heavily influenced by the opinions of his close friends, family members, and other opinions on these Websites. Because of this, internet evaluations may influence customers favorably or unfavorably. Product manufacturers use agents to divert potential buyers by spreading false information about their products or quality products. Identifying bogus reviews is crucial for new buyers and manufacturers of high-quality products.
Therefore, automatically identifying inaccurate and false reviews is a basic challenge for online review systems. This challenge is sometimes called the "fake review detection" issue. Detecting review fraud is a critical problem with various high-impact finance, health care, security, and review management applications. Even though several strategies for identifying fake reviews have been developed in recent years, these traditional detection techniques fall short when spammers use straightforward concealment techniques. For instance, spammers may pose as regular users by posting real reviews intermingled with bogus ones, making it challenging to tell one from the other. First, a face review may not be noticed since a disguised account usually behaves. This book covers the detection and the challenge of identifying fake reviews and opinions. Also, contextual and behavioral elements of reviews, fake opinion/review detection issues, recent research works, problem statements, and study objectives will be presented as current issues of online business systems.
Identifying fraud reviews or customers in a real-time financial website is crucial because the number of fraudsters (Spammers/ Fake Reviewers) is typically much smaller than the number of legitimate users. However, out of millions or billions of reviews or comments, it will be a difficult process to identify fraudulent reviews or remarks. Most well-known online service providers ( Amazon, Yelp, Alibaba, Netflix, etc.) attempt to increase their productivity by preventing fake reviews from affecting their services. In this book, we will address the most well-known challenges that refer to the task of fake reviews detection:
• Lined Reviews: These reviews, also known as (camouflaged Reviews), are made when spammers pose as normal users by posting legitimate reviews mixed with fraudulent ones.
• Redundant Account: When spammers employ origin accounts to post their fake reviews, it will show links between fake comments and those accounts.
• Fraudsters Trading: this challenge is also called (lack of necessary information), and it happens when fraudsters (spammers) avoid trading with each other to be not detected.
• Noise Identity: when fraudsters (spammers) fabricate noise information about them (such as personal photo, name, affiliation, etc.) to make it hard to identify them.
• Lack of Traceability: This challenge pretends that when users do not disclose correct or sufficient information about themselves, they limit their access from other businesses and users.
Impact:
The prevalence of web platforms is rapidly growing, extending to all types of businesses, with buyers and sellers shifting towards the e-market. The abundance of e-commerce websites has broadened users' product selection options, expanding the merchant/seller business on these platforms. Before purchasing everyday products, it is common for individuals to seek advice from their friends and family. However, millions of reviews, opinions, and suggestions from users worldwide are available on an internet platform. As a result, a customer's decision-making process is heavily influenced by user reviews, which can impact the financial profits or losses of the product provider. A review is always real in the eyes of the purchaser, but the buyer is unaware that reviews can be fake.
Audience:
This book is tailored for a diverse audience engaged in various aspects of the digital landscape, from consumers and online shoppers to cybersecurity professionals, data scientists, marketers, and business owners. It addresses the growing concern of fraudulent activities such as fake opinions and voting that impact online product reviews and recommendations.
1.Consumers and Online Shoppers:
Everyday consumers who rely on online reviews and opinions to make informed purchasing decisions.
Individuals seeking guidance on identifying trustworthy product reviews in an era of increasing digital deception.
2. Business Owners and Marketers:
Entrepreneurs and business owners aiming to maintain the integrity of their products and brand reputation.
Marketing professionals looking to understand and combat the challenges posed by fraudulent online activities.
3. Cybersecurity Professionals and Data Scientists:
Cybersecurity experts interested in staying ahead of evolving online threats, including deceptive practices in digital reviews.
Data scientists seeking techniques and methodologies for analyzing and detecting fraudulent patterns in online voting and opinions.
4. E-commerce Platforms and Review Aggregators:
Professionals working within e-commerce platforms and review aggregator websites responsible for ensuring the reliability of their platforms.
Those involved in creating and implementing algorithms to filter out fraudulent content from user-generated reviews.
5. Academics and Researchers:
Researchers in the fields of cybersecurity, data analysis, and digital marketing exploring the latest trends and advancements in detecting online fraud.
6. Academics teaching courses related to cybersecurity, digital ethics, and consumer behavior in the digital age.
7. Policy Makers and Regulatory Bodies:
Policy makers and regulatory bodies concerned with consumer protection and fair trade practices in the digital space.
Professionals involved in creating and enforcing regulations to combat deceptive practices in online reviews.
8. Certainly! Here's a description of the potential audience for a book related to the techniques of identifying fraudulent voting and fake opinions regarding online products:
This book is ideal for a diverse range of readers who have an interest in understanding and combating fraudulent activities in the digital landscape, specifically related to voting manipulation and fake opinions in online product reviews. The primary audience for this book includes:
1. Consumers and Online Shoppers: Individuals who regularly engage in online shopping and rely on product reviews to make informed purchasing decisions. They seek to gain insights into the techniques used to identify fraudulent voting and fake opinions, empowering them to make more reliable and trustworthy choices when purchasing products or services online.
2. Online Platform Operators: Professionals responsible for managing and maintaining online platforms, review websites, or e-commerce platforms. They are interested in understanding the fraudulent practices that can undermine the credibility of their platforms and are eager to learn countermeasures to detect and prevent such fraudulent activities.
3. Digital Marketing and Branding Professionals: Marketing and branding experts who are involved in managing online reputations and promoting products online. They aim to identify and mitigate the negative impact of fraudulent voting and fake opinions on brand reputation and customer trust. This book will provide them with valuable insights and techniques to combat these challenges effectively.
4. Researchers and Academics: Scholars, researchers, and students focused on the fields of data analysis, digital marketing, cybersecurity, and online behavior. They are interested in understanding the underlying techniques and methodologies used to detect and analyze fraudulent voting and fake opinions. This book can serve as a reference for their research and academic endeavors.
5. Law Enforcement and Regulatory Agencies: Professionals working in law enforcement or regulatory bodies responsible for monitoring and enforcing regulations related to online fraud, consumer protection, and fair competition. They require a comprehensive understanding of the techniques used to identify and investigate fraudulent activities in the digital realm.
this book caters to a broad audience encompassing consumers, online platform operators, marketing professionals, researchers, and law enforcement personnel who are eager to gain knowledge about the techniques and strategies to identify and combat fraudulent voting and fake opinions in the context of online products.