مصطفی احمدزاده

Big-tech corporations like Google, Meta, Microsoft etc. extensively utilize customization to collect and analyze user data, a practice integral to their business models. Google leverages user data to personalize services across its platforms, notably in its search engine and YouTube, to enhance user experience and bolster its targeted advertising strategies. Similarly, Meta uses algorithmic content curation on Facebook and Instagram, tailoring user feeds to individual preferences and behaviors, thereby generating detailed user profiles for marketing purposes. Microsoft's approach, particularly with Office 365 and LinkedIn, focuses on productivity enhancements while also gathering user data for feature refinement and targeted advertising. These practices, I argue, while improving user engagement, raise significant privacy concerns. The extensive data collection often occurs without full transparency or user consent, leading to debates about ethical implications, digital surveillance, and societal impacts. In response, there is a growing demand for stricter data governance and privacy regulations, as seen in initiatives like the GDPR and CCPA, aiming to balance the benefits of personalization with the rights and privacy of users.

Over the last decade, the retail industry has had a phenomenal growth. All figures show their success and efficiency and many studies have shown the role of customer reviews in encouraging ambivalent purchasers to buy items online. There have been numerous studies on why people read and trust these comments and taking for granted the important role of customer reviews in determining buying decision, this study endeavors to identify and explain the different factors involved in making a comment “useful.” We took an Iranian retail website and collected comments on perceived “usefulness” of each review. Our results showed that perceived level of usefulness was related to the word count of the comments, personal experience of the writer with the product, emotional description of the product, and mentioning the strength/weakness points of the product.