Introduction
Social media has become an essential part of cultural consumption, social communication and interaction, and public discourse. Recommendation algorithms on TikTok, Facebook, and Twitter, among other social media platforms, determine what content is displayed to users and what they engage with every day. Such an algorithm-based reality fosters echo chambers, cognitive bubbles, and, in the opinion of some scholars, social polarization and cancel culture. These digital environments also intensify the problems related to cognitive dissonance, that is, when people have contradictory beliefs or attitudes. Solving these problems implies having strong media and scientific literacy to enhance the overall understanding of how social media affects people’s perceptions and actions. Various media sources help in understanding the relationship between cognitive dissonance and the role of media and scientific literacy in understanding and mitigating the effects of social media algorithms on culture and society.
Source 1
A. Scientific explanation and representation
The NPR article by Mosley “How Social Media Algorithms ‘Flatten’ Our Culture by Making Decisions for us” gives a good background on how algorithms affect cultural consumption. The primary argument relates to the idea of social constructs discussed in Chapter 2 of the text. In Chapter 2, the concept of social construction implies the understanding of how social reality is constructed based on shared beliefs and interactions. These constructs provide people with a framework for perceiving reality and acting upon it by prescribing what is appropriate, typical, or significant within a given culture (Wade Chapter 2). Algorithms can be regarded as a modern form of social construct in the sense that they influence our perception and interactions with cultural content by providing a filtered view of reality. The article reflects the current state of knowledge by describing how these algorithms affect our interactions with culture and make it more uniform and less diverse, which corresponds to the concept of social constructs as being powerful and reflecting the collective perception of reality.
B. Scientific Accuracy
Mosley provides evidence for its claims by citing the work of Kyle Chayka and referencing his book “Filterworld.” Chayka argues that algorithms make consumers more passive, and this is supported by the scientific understanding that culture endures because it is collective and cannot be easily changed one person at a time. The discussion of the article regarding how algorithms influence content generation and consumption aligns with the scientific understanding of how social constructs influence behavior and culture.
C. Partisan Bias
The article has a low level of partisan bias. It does not take a political side in presenting the advantages and disadvantages of using algorithms to generate content. The emphasis is made on the cultural and social aspects of algorithmic selection rather than on the political aspect. This neutrality makes the article credible and puts it in the “Middle” bias.
D. Variability and Reliability
Mosley’s article is accurate and comprehensive in its coverage. It uses expert opinions, literature citations, and a comprehensive discussion of the topic, thus fitting the ‘Thorough Fact Reporting or Fact-Dense Reporting’ category (Fox-Ramirez). The variation of the article is kept up by the representation of other opinions, such as the possibility of algorithms in making content creation more accessible and the negative aspects of passive consumption.
Source 2
A. Scientific Explanation and Representation
The article titled “The biggest ways TikTok has changed American culture,” by Willingham, Asmelash, and Scottie published by CNN gives a comprehensive analysis of TikTok’s impact on American culture. It relates to the idea of social constructions discussed in Chapter 2 of the book, describing how TikTok influences actions, sectors, and phenomena. The article reflects the scientific perspective in its analysis of how fame and business models, and consumer behavior are influenced by TikTok’s algorithm-driven content curation, which aligns with the notion that social constructs determine norms and behaviors.
B. Scientific Accuracy
Willingham, Asmelash, and Scottie provide concrete examples and statistics to back the arguments, for instance, the use of viral videos to gain stardom and the effect on sectors like publishing and music. It effectively captures the nature of virality and the impact of algorithms in relation to trending topics and issues, which is consistent with scientific understanding of social constructs. The part where TikTok is said to be learning the users’ preferences in real-time is scientifically correct and underscores the impact of algorithms in constructing societies.
C. Partisan Bias
The article is somewhat partisan, which is characteristic of sources that are considered to “lean left” or are rated as “strong left” (Fox-Ramirez). This is seen in the emphasis on certain cultural effects and the struggle for recognition by minorities. The article is left-leaning since it focuses on cultural and social shifts influenced by TikTok, discusses diversity and inclusion, criticizes consumerism and fast fashion, raises awareness of social issues, and questions the entertainment industry’s obsession with virality over substance. These themes are consistent with liberal ideologies that are commonly associated with liberal or left-wing political views.
D. Variability and Reliability
The article falls under the “Analysis or Wide Variation on Reliability” category. It offers an overview of how TikTok has influenced different industries but may not be as detailed or analytical in some areas as in others. Although it provides different views and professional opinions, which makes it more authoritative, the inconsistency in the extent of information provided may reduce the reliability. The article covers many aspects of TikTok’s impact, such as shifting fame paradigms and upending industries like music and publishing, but the depth of the examination may differ at certain points.
Source 3
A. Representation of Current Scientific understanding
The article from the Daily Mail “Cancel culture is like a medieval mob’: Rowan Atkinson blasts social media and blames it for widening divisions in society as he hints that he could return in his role in Blackadder” by Ruby mainly focuses on sharing Rowan Atkinson’s own views and stories about cancel culture and social media rather than providing a comprehensive scientific study. Atkinson’s opinions, like referring to social media as the “digital equivalent of the medieval mob,” are compatible with the topics discussed in social psychology regarding the impact of social networks on groups and the division of society. However, the article does not contain any links to scientific works or theories that would back up these statements. This absence of empirical data complicates the assessment of how well the article reflects the state of knowledge in the field at the time of writing.
B. Scientific Accuracy
From the perspective of scientific credibility, the article fails to deliver since Atkinson provides no data or links to scientific studies to support his statements. His claims concerning the role of social media in shaping a simplistic, black-and-white perception of society cannot be considered scientifically backed, as they are more of a metaphorical nature. Ruby gives the reader an insight into what Atkinson believes and gives a clear account of his beliefs, but it does not compare his beliefs with scientific facts. This is different from Media Effects Theory, which focuses on how media shapes public opinion and conduct, as the article does not offer empirical evidence to support Atkinson’s criticism of social media’s detrimental impact. The CNN article provides a good cultural perspective but lacks strong scientific support, while the Daily Mail article presents its opinions with little scientific evidence.
C. Partisan Bias
The partisan bias in this article is right leaning, which is conservative, as it condemns cancel culture and social media. The article focuses on the negative outcomes of these phenomena, which correspond to the conservative views on free speech and censorship, without providing opposing opinions. In comparison to other left-oriented sources, this article is more negative about the effects of social media on society. According to Social Identity Theory, this bias can be explained by what Ruby mentions that the algorithms of social media platforms contribute to the establishment of echo chambers that foster division a point made by conservatives about social media. As far as partisan bias is concerned, Mosley’s is not very partisan since it mainly relies on data and research findings. Willingham, Asmelash, and Scottie’s article is left-leaning as it focuses on TikTok’s cultural influences in a positive manner, while Ruby’s article is right-leaning as it condemns social media and cancel culture from a conservative perspective.
D. Variability and Reliability
Regarding variability and reliability, Ruby’s article is highly subjective and relies mostly on Atkinson’s opinions rather than an objective analysis of the issue. This minimizes its flexibility since it does not cover a broad range of views or information. The credibility of the article is moderate; even though it gives the reader Atkinson’s opinion, it lacks scientific data and analysis. Another factor that affects the reliability of Ruby’s is its bias and sensationalism. The idea of Echo Chambers is discussed indirectly, where social media users are mainly surrounded by information that supports their existing views, thus causing polarization and intolerance, as described by Atkinson.
Academic Sociological Conclusion
The research on the role of social media algorithms in cultural consumption and public debate demonstrates the extent to which these digital technologies affect cultural practices. Education in science and media is important in reducing the impact of cognitive dissonance, which is experienced when one is confronted with information that challenges one’s beliefs. A more informed public, with the capability to decode media content and the knowledge of the algorithms at play, is in a better place to deal with the modern information environment. This literacy reduces the negative impact of echo chambers, fosters a more constructive public debate, and improves society’s capacity to respond to social, political, and cultural issues. Thus, society can learn to interpret the effects of social media through scientific and media literacy in order to enhance the life chances and social conditions of people influenced by these ubiquitous digital agents.
Reference
Fox-Ramirez, Erin. “Ad Fontes Media Releases New Media Bias Chart.” Ad Fontes Media. (2024). Retrieved From: https://adfontesmedia.com/media-bias-chart-jan-2024/
Mosley, Tonya. “How social media algorithms ‘flatten’ our culture by making decisions for us.” NPR. (2024). Retrieved From: https://www.npr.org/2024/01/17/1224955473/social-media-algorithm-filterworld
Ruby, Jeniffer. “Cancel culture is like a medieval mob’: Rowan Atkinson blasts social media and blames it for widening divisions in society as he hints that he could return in his role in Blackadder.” The Daily Mail. (2021). Retrieved From: https://www.dailymail.co.uk/news/article-9113095/Rowan-Atkinson-blasts-social-media-blames-widening-divisions-society.html
Wade, Lisa. Terrible Magnificent Sociology: with Registration Card. WW Norton & Company, 2021.
Willingham, AJ., Asmelash, Leah., and Andrew, Scottie. “The biggest ways TikTok has changed American culture.” CNN. (2023). Retrieved From: https://edition.cnn.com/2023/04/02/us/tiktok-american-culture-effects-cec/index.html
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