As we all continue to use social media more and more, echo chambers become more and more prevalent. We dive deep into the topic.
Previously, Youth Time covered several pieces on media literacy, technological advancements impact in today’s journalism and the crucial role of the media state in a democratic, free country.
We have spoken to journalists and media experts about the burdens of reporting during a pandemic, about data journalism, regarding how the media’s role as the fourth estate is shifting, and nevertheless to what extent social media is affecting public opinion and sphere.
After carefully consulting these pieces, there’s one common marker laying among almost all of them.
Echo chambers are an emerging effect from users’ behaviour and feed algorithms.
Users tend to acquire information they like the most and ignore dissenting information and join a group of like-minded peers where they frame and reinforce the shared narrative – a frequent practice where readers are only shown news content supporting their existing beliefs and preferences, without ever challenging them to think differently.
Echo chambers refers to an information bubble around readers. In this world, one is solely exposed to articles, information and content that supports their previous thinking and perspective.
When talking about such phenomena, we have to bring into discussions the algorithms present in social media platforms, such as; Facebook, Twitter and Instagram.
Different Media Outlets Cause Different Levels of Segregations
Echo chambers can happen anywhere, however some critics of online journalism are concerned about the spread of this phenomenon especially nowadays in the digital area.
The echo chamber effect on social media, is a substantial, influential paper on this issue.
It explores the key differences between the main social media platforms and how they are likely to influence information spreading and the formation of echo chambers.
To assess the different dynamics, researchers performed a comparative analysis on more than 100 million pieces of content concerning controversial topics (e.g., gun control, vaccination, abortion), from Gab, Facebook, Reddit, and Twitter.
Walter Quattrociocchi, Ph.D, Associate Professor in Computer Science, head of the of the Data and Complexity for Society Lab at Sapienza Università di Roma, and one of the authors of this paper, during a virtual meeting, further elaborated that the analysis focuses on two main dimensions:
- homophily in the interaction networks and;
- bias in the information diffusion toward like-minded peers.
He acknowledges that the paper highlights that different types of media sites have different levels of segregation, and that such differences can be associated with the degree to which users can modify what is shown to them.
Its results show that the aggregation in homophilic clusters of users dominates online dynamics.
However, a direct comparison of news consumption on Facebook and Reddit shows higher segregation on Facebook.
“While looking at our data, we found differences in levels of segregation. The highest was found on Facebook and Twitter.
“Moreover, we also found a clear difference between sites where users could tweak their feed to edit the types and amounts of posts they saw—more tweaking tended to mean less segregation. Facebook, notably, does not have such an option, while Reddit’s tweaking options are very strong.
“Hence, higher segregation was found on Facebook than on Reddit.”
Fake news Travels Faster
While talking about the implications of this practice in the future of journalism, Quattrociocchi mentions that there was a lot of discussion on this topic.
Initially, he recalls what Echo chamber represents.
“Online we can access an unprecedented amount of information without mediation. We end up in finding the sources fitting our worldview and there we meet pal that share the same vision.
“Echo chambers are the large amount of information we can access plus our selection capabilities that are being filtered from us.
“They are a group through which we joined like-minded people.”
Moreover, he emphasises an interesting fact: Fake news travels faster than real news.
“In an information ecosystem dominated by social media (designed for entertainment and to sell ads.
“The image with more likes on Instagram is an egg. It’s hard to say what is fake and what is real. […] and complexity is hard to communicate in an environment.
“We selected four platforms. The echo chambers effect on Facebook, Twitter, Reddit and Gab.
“We applied a simple definition of echo chambers, which means you MOSTLY interact with sources with your identical things and with users with similar political alignments.
“It’s the same information concept and diet. We analysed content regarding different important topics, such as; gun control violence, vaccination, and abortion.”
Moreover, he illustrates that this huge analysis found that the segregation of users is stronger in platforms if there is an algorithm pushing the information to the people.
“Reddit and GAB’s situation is different.
“The information spreading changed with social media, you have to adapt to the business model dominated by the algorithm. Information tends to foster deformation or segregation of polarised groups.”
With this being said, Quattrociocchi moves to an important, related impact of Echo Chambers: misinformation and polarisation.
Echo Chambers and Misinformation
Quattrociocchi strongly believes that there is a connection between Echo Chambers and their impact in causing misinformation and a possible polarization between two possible opposing tabors.
Users clustered in groups about narratives do not really look for the truth, but for the information/interpretation better fitting to their world-view.
In such a configuration the more the polarisation the more the possibility for fake news to spread.
“Of course, Echo chambers are polarization and polarization is Echo chambers. This affects the fake news, the kind of information we look online, it’s like propaganda. If u look at debate, then everything that’s not in my propaganda is fake news.”
In a conclusive note, he believes that the most important ingredient or solution is our awareness or the way we see things we encounter online.
“People have to be aware that it’s an emerging effect of the online world. The best way is to know how to process information while online, where we are looking for the information matter. The more we are aware the better.”
Walter Quattrociocchi is Associate Professor at Sapienza University of Rome where he leads the Centre of Data Science and Complexity for Society (CDCS).
His research interests include data science, network science, cognitive science, and data-driven modelling of dynamic processes in complex networks.
His activity focuses on the data-driven modelling of social dynamics such as (mis) information spreading and the emergence of collective phenomena.
Dr. Quattrociocchi has published extensively in peer reviewed conferences and journals including PNAS.
The results of his research in misinformation spreading have informed the Global Risk Report 2016 and 2017 of the World Economic Forum and have been covered extensively by international media including Scientific American, New Scientist, The Economist, The Guardian, New York Times, Washington Post, Bloomberg, Fortune, Poynter and The Atlantic.
He published two books: Misinformation. Guida alla società dell’informazione e della credulità (Franco Angeli) and Liberi di Crederci. Informazione, Internet e Post Verità with Codice Edizioni for the dissemination of his results.
In 2017 Dr. Quattrociocchi was the coordinator of the round table on Fake News and the role of Universities and Research to contrast fake news chaired by the President of Italy’s Chamber of Deputies Mrs Laura Boldrini.
Since 2018 he is Scientific Advisor of the Italian Communication Authority (AGCOM) and currently Member of the Task Force to contrast Hate Speech nominated by the Minister of Innovation.
He is regularly invited for keynote speeches and guest lectures at major academic and other organizations, having presented among others at CERN, European Commission, the University of Cambridge, Network Science Institute, Global Security Forum etc.
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