Based on the background materials, explain and provide an ex…

Based on the background materials, explain and provide an example of how “filter bubbles” can influence peoples’ attitudes and beliefs. Cite your sources and use the proper media psychology terminology in your initial discussion posting.

Filter bubbles can have significant effects on individuals’ attitudes and beliefs, shaping their worldview and limiting exposure to diverse perspectives. The concept of filter bubbles refers to the personalized information bubbles created by algorithms and online platforms, which selectively present content based on users’ online behavior and preferences (Pariser, 2011). This phenomenon can lead individuals to encounter predominantly familiar and reinforcing information, thereby creating a biased perception of the world.

Filter bubbles are a result of algorithms commonly used by social media platforms, search engines, and news aggregators. These algorithms rely on user data such as search history, browsing patterns, and online interactions to create personalized content recommendations. As a consequence, users are more likely to be exposed to information and viewpoints that align with their pre-existing beliefs, interests, and preferences.

One example of how filter bubbles influence attitudes and beliefs can be seen in the context of political polarization. Studies have shown that individuals who are exposed to primarily ideologically aligned content develop stronger, more extreme political attitudes (Bakshy, Messing, & Adamic, 2015; Barberá, 2015). Filter bubbles can reinforce and amplify political beliefs by presenting individuals with content from sources that align with their existing views, while filtering out dissenting opinions or alternative perspectives. This selective exposure to information can lead to a lack of critical evaluation and a reinforcement of pre-existing biases.

For instance, imagine two individuals with opposing political views who rely on social media platforms as their primary source of news. Due to the filter bubble effect, their social media feeds would likely show them different news stories, articles, and opinions based on their political affiliations. Person A, who leans more conservative, might see news articles from conservative media outlets that support their political beliefs, while Person B, who leans more liberal, might be exposed to content that aligns with their own perspectives. This constant exposure to ideologically aligned content would reinforce their existing beliefs and potentially contribute to the entrenchment of their viewpoints. As a result, both individuals might become less open to considering alternative positions, leading to increased political polarization.

Pariser (2011) suggests that filter bubbles can have broader implications beyond politics, encompassing diverse areas such as culture, ideology, and even daily life choices. For instance, an individual who frequently searches for and reads articles about healthy eating may be presented with online recommendations for organic food recipes and vegan lifestyles. This information bubble could reinforce their belief in the benefits of organic and vegan diets, while potentially disregarding alternative perspectives or critical viewpoints.

This phenomenon is reinforced by the concept of selective exposure, which suggests that individuals actively seek out information that confirms their pre-existing beliefs and attitudes while avoiding information that challenges or contradicts them (Iyengar & Hahn, 2009). Filter bubbles amplify selective exposure by algorithmically curating content that aligns with users’ existing preferences. The result is that individuals remain within their comfort zones and experience a confirmation bias, as their beliefs and attitudes are constantly reinforced without encountering dissenting perspectives.

In conclusion, filter bubbles play a crucial role in shaping individuals’ attitudes and beliefs by limiting their exposure to diverse perspectives. These online information bubbles created through personalized algorithms can lead to reinforcement of pre-existing beliefs, political polarization, and a confirmation bias. Understanding the influence of filter bubbles is important to identify the potential consequences they have on individuals’ perception of the world and the formation of their attitudes and beliefs.