Filter bubbles and echo chambers

In modern times, people have instant access to a great amount of information, and this is the reason for information overload. The methods of managing this amount of information, such as personalization, have brought other problems with them. The recommendation algorithm's predictions about users' preferences potentially hide part of the content, this is called a filter bubble effect. Furthermore, personalization is a very useful tool to increase sales and a very nice way for people to save time and avoid negative emotions. This fact only deepens the problem of filter bubbles because it means that it is encouraged by natural human behavior. Repeated exposure to the same content as a result of the filter bubble effect leads to reinforcement of users' own opinions on a topic, which is a sign of the echo chamber effect. The purpose of this work is to analyze and compare the effects of filter bubbles and echo chambers, and to determine their relation, differences and occurrences. Methods that have been used to achieve the stated goals are observation, analysis and review of available research and scientific articles and comparison. This work described different possible areas of occurrence of filter bubbles and echo chambers, reasons for their occurrence, possible threats and methods of prevention. The practical part of the study was dedicated to investigating the occurrence of filter bubbles in Google search engine and comparing the differences between searching as a signed-in user and as a non-signed-in user. The conducted research confirmed or provided a further illustration of possible occurrences of such phenomena as hiding part of the results due to personalization, information narrowing and filter bubbles.