How Big Data and Social Media Algorithm Systems Shape Consumer Intentions: A Critical Study on Personalization, Platform Power, and Digital Influence

Abstract

With the rapid development of artificial intelligence, big data and algorithmic recommendation systems, social media platforms have gradually become some of the leading digital environments in recent years. TikTok, Instagram and Xiaohongshu systematically track user engagement metrics - including watch, likes, comments, and click- through rates-to feed their algorithmic recommendation engines. Algorithmic recommendation systems can be used by these platforms to deliver content and personalised advertisements more precisely. Although it is good for the use of platforms by the public, at the same time, serious issues have been pointed out, such as manipulation and loss of freedom for users. Big Data and Algorithmic Systems' Influence on Consumer Behavioural Intentions in Social Media Platforms. In terms of the theory of surveillance capitalism and platform capitalism and algorithmic governance, how personalized recommendation systems have affected consumer behaviour is analyzed in this paper. TikTok and Instagram have been used as the main subjects of study to investigate the effects of emotional content, data collection, influencer culture and behavioural prediction on people's consumption behaviour. Algorithms have been developed to predict what people will want; now they actively shape people's wishes by presenting personalised information and products over and over again. Social media platforms attract more users by using emotional triggers, an endless-scroll design, and precise-target ads. As people use the Internet more and more often, the types of products they need gradually start to change. At the same time, algorithmic recommendation systems are also associated with problems such as "filter bubbles", information homogeneity, privacy concerns and reduced user autonomy. Although users have the choice, the information they receive will be filtered by algorithms in the major platforms first. Therefore, the platform is not an impartial technological system, but rather a kind of digital power that collects data and changes behaviour. Today, the economy of social media is closely linked to forms of digital control and surveillance, as shown in the paper. Although the platforms gain profits from users' behaviour data, they are also constructing new social values and consumer cultures. Finally, this paper proposes increasing the transparency of algorithms, promoting digital literacy among the public, and strengthening regulatory measures for data collection.