Analysis Of the Impact of Information Filtering on People's Thinking--Take Filter Bubble as An Example

Abstract

The term "filter bubble" refers to the personalized information bubble that presents users with content that aligns with their previous interests and beliefs, which is created by algorithms that cater content to an individual's preferences and past behavior. Filter bubbles make it easier for people to find information, but improper use can lead to limited and biased perceptions of the world. For example, individuals may miss out on different perspectives and important information by only being exposed to information that aligns with their existing views. Therefore, paying attention to giving play to its positive role is necessary. Based on this, this paper argues that effective measures should be taken to prevent the negative effects of filter bubbles. First of all, it is necessary to pay attention to the optimization algorithm to avoid the fixed recommendation of information. Individuals should pay attention to making full use of information channels to obtain different information, and at the same time, people should pay attention to maintaining their thinking.