In the era of information explosion, we leave countless digital footprints on the Internet every day: clicked links, stayed pages, browsed goods and published remarks. These seemingly disorganized data, like scattered pearls, can be connected in series into a clear portrait of users in the eyes of a special "treasure hunter", which is big data. Big data, a powerful tool, is excavating and predicting our preferences with unprecedented depth and breadth.

The core of big data mining user preferences lies in its powerful data collection, processing and analysis capabilities. It not only simply counts what users clicked, but also makes deep correlation and cross analysis of these behavioral data. For example, a user frequently searches for outdoor hiking equipment, and at the same time follows several well-known travel bloggers on social media, and often buys energy bars and sports drinks on shopping platforms. The big data system will integrate these seemingly unrelated behavioral data to form a clear portrait: this user has a strong interest in outdoor sports and travel.

This analysis process is usually divided into several key steps. The first is data collection, which collects user behavior data from various channels, including browsing history, searching keywords, purchase records, social interaction and so on. The second is data cleaning and integration, which standardizes these data from different sources and formats, removes redundancy and error information, and prepares for subsequent analysis. The most critical step is data modeling and algorithm application. At this stage, data scientists will use algorithms such as machine learning and deep learning to identify and predict patterns of data. For example, collaborative filtering algorithm will analyze other users with similar interests and recommend their favorite products; The content filtering algorithm will recommend similar new products for you according to the characteristics of products you liked in the past.

Behind these algorithms are models trained from massive data. It can identify preferences that we are not aware of. For example, you may only click on the promotional film about science fiction movies occasionally, but the big data system may judge that you are potentially interested in this type and start pushing relevant movie information and peripheral products to you. It can even infer your mood and purchase intention through your browsing time, clicking frequency and other subtle actions, so as to send you the most accurate "temptation" at the most appropriate time.

Of course, this deep excavation has also triggered a discussion about privacy and ethics. When we enjoy the convenience brought by personalized recommendation, we also need to realize that every digital behavior of ourselves is being recorded and analyzed. Our preferences, habits, and even potential consumption tendencies may become part of business strategy. Therefore, understanding how big data works is not only an insight into the development trend of science and technology, but also a necessary ability to protect yourself in the digital age. In the end, big data doesn't really have insight into our souls, but its powerful analytical ability is enough to paint an accurate portrait of our digital behavior.

（Writer：Haicy）