Filter Bubbles Research Articles

Understanding the Contribution of Recommendation Algorithms on Misinformation Recommendation and Misinformation Dissemination on Social Networks

Social networks are a platform for individuals and organizations to connect with each other and inform, advertise, spread ideas, and ultimately influence opinions. These platforms have been known to propel misinformation. We argue that this could be compounded by the recommender algorithms that these platforms use to suggest items potentially of interest to their users, given the known biases and filter bubbles issues affecting recommender systems. While much has been studied about misinformation on social networks, the potential exacerbation that could result from recommender algorithms in this environment is in its infancy. In this manuscript, we present the result of an in-depth analysis conducted on two datasets ( Politifact FakeNewsNet dataset and HealthStory FakeHealth dataset ) in order to deepen our understanding of the interconnection between recommender algorithms and misinformation spread on Twitter. In particular, we explore the degree to which well-known recommendation algorithms are prone to be impacted by misinformation. Via simulation, we also study misinformation diffusion on social networks, as triggered by suggestions produced by these recommendation algorithms. Outcomes from this work evidence that misinformation does not equally affect all recommendation algorithms. Popularity-based and network-based recommender algorithms contribute the most to misinformation diffusion. Users who are known to be superspreaders are known to directly impact algorithmic performance and misinformation spread in specific scenarios. Findings emerging from our exploration result in a number of implications for researchers and practitioners to consider when designing and deploying recommender algorithms in social networks.

Which Democratic Way to Go?

There are concerns amongst researchers and the general public that social media platforms threaten democratic values. Social media corporations and their engineers have responded to these concerns with various design solutions. Though the objective of designing social media democratically sounds straightforward, the concrete reality is not. The authors discuss what a democratic design for social media platforms could look like by exploring two classical conceptions of democracy, one in the liberal tradition and the other in the deliberative tradition. In particular, they discuss three concerns: 1) mis- and disinformation; 2) hate speech; and 3) the relations between filter bubbles, echo chambers, and public debate. By describing the underlying ideals of the two traditions and translating these into design guidelines, the authors make explicit how varied and contrary the implications of different conceptions of democracy can be for addressing public concerns and designing for democratic social media. With these things in mind, this article responds to a call, which is to raise awareness among social media corporations, engineers, and policymakers about varying democratic ideals and the implications that these may have for social media.

Acoustical characterization of concentrated bubbly media

Bubbles are known to be strongly resonant acoustic scatterers. As such, their presence in a fluid, even for amounts of gas as low as 1%, highly impacts the propagation of acoustic waves. Ultrasounds are, thus, a great tool for bubble distribution measurements in opaque fluids. Additionally, diluted media models have been shown to have a good agreement with experiments at volume fraction below 1%. One of the aims of our study is to determine the limit volume fraction beyond which the models start to fail. To achieve that, we measure relfection and transmission of ultrasounds through bubbly media ranging from 5% to 60 % of gas volume fraction. Samples are polydisperse thin slabs with median radii ranging between 30 and 180 μm. Alongside experimental measurements, numerical simulations are carried out with monodisperse distributions. Up to 10%, we find a good agreement between the independent scattering approximation and our experimental results.

Pandemic and infodemic: the spread of misinformation about COVID-19 from a cultural evolutionary perspective

In this paper, we critically consider the analogy between “infodemic” and “pandemic”, i.e. the spread of fake news about COVID-19 as a medial virus and the infection with the biological virus itself from the perspective of cultural evolutionary theory (CET). After confronting three major shortcomings of the ‘infodemic’ concept, we use CET as a background framework to analyze this phenomenon. To do so, we summarize which bi-ases are crucial for transmission in terms of cultural selection and how transmission is restricted by filter bubbles or echo chambers acting as TRIMS (transmission isolating mechanisms) post “infection”, which isolate false from trustworthy scientific information in the context of the Corona pandemic. This is followed by a demonstration of the threat to biological fitness posed by the effects of an infection with fake news, which leads to a reduced willingness to vaccinate and follow health measures. We identify fake news on Covid as pseudoscience, trying to immunize itself from external influences. We then address the question of how to combat the infodemic. Since debunking strategies, such as warnings by fact-checking, have proven relatively ineffective in combating fake news, the inoculation theory from psychology might offer an alternative solution. Through its underlying ‘prebunking strategy’, which educates individuals about the risks and tactics of fake news prior to a potential infection, they could be ‘immunized’ in advance, similar to a virological vaccination. Although we recognize that the pandemic/infodemic analogy is in fact far from perfect, we believe that CET could provide a theoretical underpinning in order to give much more semantic depth to the concept ‘infodemic’.

The public sphere in the mode of systematically distorted communication

The contemporary proliferation of “filter bubbles” and “echo chambers” seems to render obsolete the notion of a public sphere in the singular. In my article, I would like to argue against this view: Following Jürgen Habermas, “the public sphere” can be understood as the concomitant horizon of communicative action, while the latter permeates society as a whole. On the basis of this socio-philosophical approach, the omnipresent tendencies toward fragmentation appear as reactive attempts to ward off this socially established and context-transcending context of discussion. Habermas himself, however, has never adopted this perspective. Instead, he interprets the various symptoms of the decline of the public sphere—including its fragmentation—as the result of a “colonization of the lifeworld” by economic, bureaucratic, and technological system logics. However, on the basis of the concept of “systematically distorted communication,” which was still crucial for Habermas’s early work, it is possible to reconstruct how the lifeworld context of communicative action, out of which the public sphere emerges, is not only corroded and cut through from the outside by system logics but also exhibits its own dialectic of the refusal of discourse and the overcoming of this refusal. The fragmentation of the public sphere that we are confronted with today can be theoretically interpreted and politically addressed as a precarious standstill of this dialectic.

How University Students Evaluate the Role of Social Media in Political Polarization: Perspectives of a Sample of Turkish Undergraduate and Graduate Students

This study aimed to find out if there is a relationship between social media and political polarization in Türkiye from the perspective of Turkish students. To reach this aim, the needed data were collected through qualitative and quantitative approaches. A total of 303 valid questionnaires were analyzed. The sample consisted of university Turkish students across undergraduate, masters, and PhD levels in Türkiye aged between 18 and 50+. As well, an online focus group discussion with six Turkish students from different universities and education levels was conducted to gain a more in-depth understanding of the study’s problem. The results of the study showed that the perspectives of the Turkish students were that social media had a weak-to-moderate effect on political polarization in Türkiye. Furthermore, the results indicated that the studied sample of the Turkish students does not rely on social media platforms to obtain political news, and most of them do not follow political leaders on social media. Moreover, communication platforms did not encourage many Turkish students to express themselves, which is an indication that social media algorithms have contributed to a medium degree in creating filter bubbles through the content they suggest to users. Results have also shown that Turkish students are afraid that their posts and comments are being censored.

The Impact of the Application of Algorithms in Social Media Marketing on Society

As algorithms have evolved, they have been heavily used in social media, and more brands are using them as an effective tool for social media marketing. The use of algorithms in social media marketing has become increasingly prevalent as brands seek to maximize their impact and reach on these platforms. However, there has been a growing concern over the impact of algorithms on society, including issues such as filter bubbles, echo chambers, and algorithmic bias. This research is important as it seeks to provide insights into the social impact of algorithmic applications in social media marketing. The findings could be useful to both brands and consumers, enabling them to make more informed decisions about their use of algorithms in social media marketing. This research aims to investigate the social impact of the use of algorithms in social media marketing. The study collected 135 samples through a qualitative research method using a questionnaire for social media users. The collected data was analyzed to derive both positive and negative impacts of algorithmic applications in social media marketing on society. The application of algorithms on social media can affect society due to efficient marketing and enhanced access to information. However, it can also have negative impacts on society, for example, potential for manipulation, loss of privacy, reinforcement of stereotypes and biases, and amplification of harmful content. And the paper builds on previous research on the subject of algorithms and social media by exploring their potential impact in more depth. By doing so, the study intends to enable both brands and consumers to effectively avoid its negative effects.

The Influence of Social-Media on Cultural Integration: A Perspective on Digital Sociology

Technological developments have made social media a part of people's daily lives. The ability of social media to cross geographical boundaries causes a culture change, especially in cultural integration. This research then aims to look at the role of social media in influencing cultural interactions in society. This research will be carried out using a descriptive qualitative approach. The data used in this research comes from various research results and previous studies that are still relevant. The results of this research then show that the presence of social media makes cultural integration more complicated. The presence of social media plays a key role but also provides new challenges in society. Therefore, the importance of wise use of social media in cultural integration is very necessary. To achieve deeper cultural integration, efforts need to be made to minimize risks such as filter bubbles, polarization, and cultural conflicts that can arise in the digital world.

CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System

While personalization increases the utility of recommender systems, it also brings the issue offilter bubbles. e.g., if the system keeps exposing and recommending the items that the user is interested in, it may also make the user feel bored and less satisfied. Existing work studies filter bubbles in static recommendation, where the effect of overexposure is hard to capture. In contrast, we believe it is more meaningful to study the issue in interactive recommendation and optimize long-term user satisfaction. Nevertheless, it is unrealistic to train the model online due to the high cost. As such, we have to leverage offline training data and disentangle the causal effect on user satisfaction.To achieve this goal, we propose a counterfactual interactive recommender system (CIRS) that augments offline reinforcement learning (offline RL) with causal inference. The basic idea is to first learn a causal user model on historical data to capture the overexposure effect of items on user satisfaction. It then uses the learned causal user model to help the planning of the RL policy. To conduct evaluation offline, we innovatively create an authentic RL environment (KuaiEnv) based on a real-world fully observed user rating dataset. The experiments show the effectiveness of CIRS in bursting filter bubbles and achieving long-term success in interactive recommendation. The implementation of CIRS is available via https://github.com/chongminggao/ CIRS-codes.

A sensemaking system for grouping and suggesting stories from multiple affective viewpoints in museums

ABSTRACT This article presents an affective-based sensemaking system for grouping and suggesting stories created by the users about the cultural artefacts in a museum. By relying on the commonsense reasoning framework, the system exploits the spatial structure of the Plutchik’s “wheel of emotions” to organize the stories according to their extracted emotions. The process of emotion extraction, reasoning, and suggestion is triggered by an app, called GAMGame, and integrated with the sensemaking engine. Following the framework of Citizen Curation, the system allows classifying and suggesting stories encompassing cultural items able to evoke not only the very same emotions of already experienced or preferred museum objects but also novel items sharing different emotional stances and, therefore, able to break the filter bubble effect and open the users’ view toward more inclusive and empathy-based interpretations of cultural content. The system has been designed tested, in the context of the H2020EU SPICE project (Social cohesion, Participation, and Inclusion through Cultural Engagement), in cooperation with the community of the d/Deaf and on the collection of the Gallery of Modern Art (GAM) in Turin. We describe the user-centered design process of the web app and of its components and we report the results concerning the effectiveness of the diversity-seeking, affective-driven, recommendations of stories.

Filter bubbles in recommender systems: Fact or fallacy—A systematic review

AbstractA filter bubble refers to the phenomenon where Internet customization effectively isolates individuals from diverse opinions or materials, resulting in their exposure to only a select set of content. This can lead to the reinforcement of existing attitudes, beliefs, or conditions. In this study, our primary focus is to investigate the impact of filter bubbles in recommender systems (RSs). This pioneering research aims to uncover the reasons behind this problem, explore potential solutions, and propose an integrated tool to help users avoid filter bubbles in RSs. To achieve this objective, we conduct a systematic literature review on the topic of filter bubbles in RSs. The reviewed articles are carefully analyzed and classified, providing valuable insights that inform the development of an integrated approach. Notably, our review reveals evidence of filter bubbles in RSs, highlighting several biases that contribute to their existence. Moreover, we propose mechanisms to mitigate the impact of filter bubbles and demonstrate that incorporating diversity into recommendations can potentially help alleviate this issue. The findings of this timely review will serve as a benchmark for researchers working in interdisciplinary fields such as privacy, artificial intelligence ethics, and RSs. Furthermore, it will open new avenues for future research in related domains, prompting further exploration and advancement in this critical area.This article is categorized under: Fundamental Concepts of Data and Knowledge > Human Centricity and User Interaction Application Areas > Internet Commercial, Legal, and Ethical Issues > Ethical Considerations Commercial, Legal, and Ethical Issues > Security and Privacy

Recontextualizing the Role of Social Media in the Formation of Filter Bubbles

Recontextualizing the Role of Social Media in the Formation of Filter Bubbles

Contingent Encounters: Understanding the Relationship Between Homophily and Polarisation within Social Media

We are witnessing a polarisation of opinions and political groupings across the world, as evidenced by the rise of populism, conspiracy theories and an increasing distrust of authority. One common theme which runs through this polarisation is the mediation of social media. I thus ask, what is it about social media that creates polarisation, and how can a philosophy of the encounter help remedy it? I argue existing understandings of polarisation online such as the filter bubble hypothesis are technologically deterministic. This determinism, I argue is confusing academic critiques of the sociological principle of homophily. To counter this position and extend our critique of homophily in network science, I propose to turn to Louis Althusser’s ‘The underground current of the materialism of the encounter’ in which he argues that contingency and openness is the material basis for freedom, thinking and the encountering of the world. With an emphasis on contingency, we can correctly ascertain how technology distorts and intervenes in the encounter. This paper aims to build on such a critical stance for analysing digital networks by reclaiming the contingency which defines true encounters and arguing that to understand polarisation means to move beyond the filter bubble hypothesis. This in turn enables a clearer understanding of the role homophily plays in causing polarisation within social media. The implications of these findings instruct us to look outside of algorithmic structure of social media and into the wider societal causes of polarisation.

Fish evacuate smoothly respecting a social bubble

Crowd movements are observed among different species and on different scales, from insects to mammals, as well as in non-cognitive systems, such as motile cells. When forced to escape through a narrow opening, most terrestrial animals behave like granular materials and clogging events decrease the efficiency of the evacuation. Here, we explore the evacuation behavior of macroscopic, aquatic agents, neon fish, and challenge their gregarious behavior by forcing the school through a constricted passage. Using a statistical analysis method developed for granular matter and applied to crowd evacuation, our results clearly show that, unlike crowds of people or herds of sheep, no clogging occurs at the bottleneck. The fish do not collide and wait for a minimum waiting time between two successive exits, while respecting a social distance. When the constriction becomes similar to or smaller than their social distance, the individual domains defined by this cognitive distance are deformed and fish density increases. We show that the current of escaping fish behaves like a set of deformable 2D-bubbles, their 2D domain, passing through a constriction. Schools of fish show that, by respecting social rules, a crowd of individuals can evacuate without clogging, even in an emergency situation.

The old-new epistemology of digital journalism: how algorithms and filter bubbles are (re)creating modern metanarratives

In journalism studies, the advent of the World Wide Web and the rise of online journalism are generally associated with going beyond the objective, normative paradigm associated with the principles of philosophical and scientific modernity towards a postmodern paradigm centred on subjectivity and relativism. This article offers an alternative reading of the epistemology of online journalism: the fragmentation of audiences into homophilic networks, the formation of ideological bubbles, and the growing polarisation caused by algorithms make the contents circulating online a reintroduction of modernity’s metanarratives. These metanarratives in no way correspond to the principles typical of postmodernism, such as the equivalence of interpretations and openness to dialogue. Journalistic content also comes under this charge: although it conveys narratives that are subjective, they are perceived as absolute truths inside the information bubbles in which they circulate. This phenomenon is caused by “information platformization” processes. Based on these premises, a new definition of online journalism is proposed: rather than “postmodern”, it can be better understood as a fulfilment of the foundational principles of modernism, but in a subjective form.

The search query filter bubble: effect of user ideology on political leaning of search results through query selection

ABSTRACT It is commonly assumed that personalization technologies used by Google for the purpose of tailoring search results for individual users create filter bubbles, which reinforce users’ political views. Surprisingly, empirical evidence for a personalization-induced filter bubble has not been forthcoming. Here, we investigate whether filter bubbles may result instead from a searcher’s choice of search queries. In the first experiment, participants rated the left-right leaning of 48 queries (search strings), 6 for each of 8 topics (abortion, benefits, climate change, sex equality, immigration, nuclear family, Islam, and taxation). An independent sample of participants were then asked to select one of these queries for each of the 8 topics. With the exception of the topic of Islam, participants were significantly more likely to select a query corresponding to their own political leaning, compared to other queries, explaining between 12% and 39% of the variance. A second experiment investigated the effect of the political leaning of the same queries on the overall political leaning of Search Engine Result Pages (SERPs) in Google Search. The top six results of each SERP were rated collectively by a third group of participants, explaining 36.3% of the variance across all 48 search terms (p < .00001). That is, (1) participants in our experiments tended to select own-side search queries, and (2) using those queries tended to yield own-side search results when using the Google search engine. Our results are consistent with the notion of a self-imposed filter bubble in which query selection plays a salient role.

Технологии социальных медиа в политической социализации студенческой молодежи

The article reveals the role of social media and modern communication technologies influencing process of political socialization of students who is an actor of innovation in society. The political socialization of students is influenced by historical events, widespread political values, and political system. It is shown that during periods of social change political norms and values are blurred, the influence of previously dominant agents and mechanisms of political socialization (families, schools, education systems) decreases, new agents of political socialization of students (reference groups, bloggers, Internet communities) come to the fore. The main tool of political socialization of students is mediated communication through social media. The influence of traditional media on young people is decreasing while at the same time the influence exerted by social media is growing. Social media itself acts as a technology for promoting various ideas including political ones. Specific types of youth involvement in politics such as online contact and direct participation are considered. The technologies of social media influence on the political socialization of young people are described that allow fragmenting the public sphere ("filter bubbles", "echo chambers", "information bunkers") forming clip consciousness which does not contribute to the reflection and holistic perception of the political picture in the world. It is emphasized that the most active participants of online communities are students who easily pick up trends and images. There are no structures in modern social networks that guarantee the minority qualitatively equal access to the advisory function of public sphere. The article shows the role of expert communities in politics, social management and influence on youth. It is noted that the expert community as a self-organizing disordered system has the property of dissipativity. The functions of the expert community are analytical, communicative, educational, predictive, ideological, innovative. The technologies of the agenda and creation of thematic groups and communities in social media are considered, political trends in thematic groups and communities are highlighted. The majority determines the agenda. There is no censorship and strict moderation political discussions. Participation transmits from offline to online sphere.

DEMOCRACY AND RULE OF LAW IN THE ERA OF ALGORITHMS: A REVIEW ON INTERNET SHUTDOWNS IN INDIA

The author of this article analyses the algorithmic impact on public participation in the decision-making process and its effects on democratic principles as recognized under the Constitution. Democratic principles are implemented through the Institutions of civil societies, and civil societies have problems with internal and external contractions and trust issues. In the contemporary world, it is observed that the government is silent on public opinion on several of its decision. This silence of government gives rise to several questions, such as – In a democratic setup, to what extent public can participate in the decision-making process of government? To what extent government can curb the voice of people with the help of assisted technologies such as internet shutdown and filter bubbles? What are the possible legitimate ways a government can be accountable for its actions?

A tale about facts and opinions: The impact of a drama intervention on middle-school students´ information literacy

Today, huge amounts of data are produced, collected, and presented in all kinds of contexts. The ability to critically examine and evaluate information and arguments in relation to empirical evidence is often referred to as information literacy. It is of utmost importance that students are adequately scaffolded to develop this ability, to be able to become democratic citizens. The study presented combines learning science and drama to explore whether this approach can make 6 grade students more aware of certain aspects of information literacy, such as false balance, the burden of proof, and filter bubbles. Half of the students watched a play and participated in a pedagogical follow-up before answering a questionnaire. The other half answered the questionnaire before the intervention. Results show that students watching the play had grasped the core of the more tangible questions, writing more elaborated and relevant answers than students in the control group.

Bioethics and artificial intelligence: between deliberation on values and rational choice theory.

The present work revisits how artificial intelligence, as technology and ideology, is based on the rational choice theory and the techno-liberal discourse, supported by large corporations and investment funds. Those that promote using different algorithmic processes (such as filter bubbles or echo chambers) create homogeneous and polarized spaces that reinforces people's ethical, ideological, and political narratives. These mechanisms validate bubbles of choices as statements of fact and contravene the prerequisites for exercising deliberation in pluralistic societies, such as the distinction between data and values, the affirmation of reasonable dissent, and the relevance of diversity as a condition indispensable for democratic deliberation.