Filter Bubbles Research Articles

I'm the same, I'm the same, I'm trying to change: Investigating the role of human information behavior in view change

AbstractInformation is powerful; it can influence peoples' views and, in turn, their behavior. Much recent research and discussion on the role information plays in view change has focused on filter bubbles, echo chambers and misinformation and how they might influence what people think and how they act. However, no prior work has focused specifically on understanding the human information behavior (HIB) that drives and facilitates view change. We report findings from interviews with 18 people who recently changed views on issues they considered important. We found a tight symbiotic relationship between HIB and view change; passive information encountering sparked change, often spurring follow‐up active seeking and verification which progressed the change to a “point of no return,” supported making the change and reinforced the decision to change. When shared, information that contributed to the change sometimes sparked changes in others (as did expressing or debating the change), serving as an information encounter that perpetuated a cycle of HIB and view change. This understanding of the integral role of HIB in view change can inform policy and systems design to promote view change autonomy and a broader research agenda of understanding HIB to support democratic principles and values.

Exploring How the Filter Bubble Effect on Twitter Influences Political Polarization and the Mediating Role of Media Literacy

The advent of social media has significantly reshaped political communication, offering unparalleled opportunities for engagement while also presenting challenges to democratic discourse. One such challenge is the emergence of filter bubbles — personalized information echo chambers created by algorithmic content curation, which have been implicated in increasing political polarization. This study investigates the influence of the filter bubble effect on Twitter on political polarization and examines the potential mediating role of media literacy. Through a mixed-methods approach, combining content analysis of Twitter interactions with survey research on media literacy among Twitter users, the study reveals a significant correlation between exposure to filter bubbles and increased political polarization. However, it also finds that individuals with higher levels of media literacy are less affected by the polarizing effects of filter bubbles. These individuals demonstrate a greater ability to critically evaluate information, seek out diverse sources, and engage in balanced political discussions. The findings underscore the importance of media literacy as a mitigating factor against the divisive impacts of filter bubbles, highlighting its potential to foster a more informed and less polarized public discourse. This study contributes to the understanding of the complex interplay between technology, media literacy, and democracy, offering insights into the challenges and opportunities for combating polarization in the digital age.

Size and pressure dependent activity of lipid coated bubbles and finite element simulation of the propgation of focused ultrasound through bubbly media

Use of nanodroplets as alternative to bubbles is limited to high pressure applications due to their high vaporization threshold (>1 MPa). For low pressure applications (e.g <800 kPa) and stable bubble activity, size isolated micron or sub-micron bubbles may be used to tackle the pre-focal bubble activity and attenuation. Numerical simulations of the Marmottant model were ran for bubble sizes of 0.45, 1, 2, and 4 μm in response to 1 MHz ultrasound with pressures between 10 and 700 kPa. All agents were volume matched to 20 μl/kg of Definity considering inter-bubble interactions. The pressure-dependent attenuation and the total acoustic power (TAP) were calculated for each population. Finite element simulations (FEMS) were run by taking account the pressure dependent attenuation and sound speed. Using size isolated bubbles an experimental passive cavitation case study was performed for the same exposure conditions and sizes. Numerical results show that TAP and attenuation of the bubbles are size dependent. Bigger bubbles have stronger responses at lower pressures. However, smaller agents exhibit a size-dependent pressure threshold behavior (PT) above which their attenuation and TAP grow stronger than their bigger counterparts in qualitative agreement with experiments. FEMS show that the PT of oscillations may be used to reduce pre-focal attenuation for ultrasound propagation with minimal loss.

The Impact of Social Media on Political Polarization

Purpose: The main objective of this study was to explore the impact of social media on political polarization.
 Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library.
 Findings: The findings revealed that there exists a contextual and methodological gap relating to the impact of social media on political polarization. Preliminary empirical review revealed that social media significantly contributes to political polarization through mechanisms like filter bubbles and echo chambers. It emphasizes the need for media literacy programs and critical thinking to navigate these platforms effectively. The implications are substantial, impacting society and democracy. Future research should delve into individual characteristics and cross-cultural variations, while policymakers and social media companies should consider transparency and algorithmic adjustments. By addressing these challenges and promoting informed discourse, we can work towards a healthier democratic environment in the digital age.
 Unique Contribution to Theory, Practice and Policy: The Filter Bubble Theory, Spiral of Silence Theory and the Selective Exposure Theory may be used to anchor future studies on political polarization. The study offered four key recommendations. Firstly, there is a need to enhance digital media literacy programs to equip individuals with critical thinking skills to discern credible information on social media. Secondly, social media platforms should prioritize algorithmic transparency and accountability to avoid inadvertently exacerbating polarization. Thirdly, promoting civil and constructive online discourse, discouraging toxic behavior, and enforcing moderation policies can foster a more inclusive online environment. Lastly, supporting independent fact-checking and news verification initiatives can help combat the spread of misinformation and promote reliance on credible sources, thereby reducing the impact of misinformation on political polarization.

The Degree of Homogeneity Versus Heterogeneity in Individuals’ Political News Consumption

Abstract: This work investigated the prevalence of filter bubble or echo chamber-related phenomena, psychological factors rendering individuals resilient or vulnerable to them, and their associations to political views focusing on extremity and polarization. For this, a cross-cultural replication of a study by Sindermann et al. (2021) was conducted. As an extension, multiple political views variables were assessed to examine whether the application of different conceptualizations of political views explains heterogeneous findings across previous studies. Two samples were recruited: 390 ( n = 135 males) US college students and a quota sample of 489 ( n = 243 males) US adults. Participants completed personality scales and measures on political news consumption homogeneity versus heterogeneity and political views. Consistent with previous research, results revealed few individuals consume political news absolutely homogeneously. Openness was negatively related to the degree of political news consumption homogeneity, and the relationship between political news consumption homogeneity and political views yielded inconsistent, often statistically nonsignificant, results. These findings challenge the prevailing notion of filter bubbles and echo chambers as widespread phenomena and indicate that relationships between political news consumption homogeneity and political views are not necessarily deleterious with respect to extremization and polarization. As such, the results suggest that these phenomena might not be as significant for the general population as previously thought. Nonetheless, certain individuals might still find themselves in filter bubbles or echo chambers and suffer from accompanying consequences. In this regard, the present work replicates findings underscoring that individuals with lower Openness exhibit greater political news consumption homogeneity.

DINAMIKA KOMUNIKASI DALAM ERA DIGITAL : TANTANGAN DAN PELUANG

This article discusses the dynamics of communication in the context of the digital era, identifying challenges that arise along with technological developments, as well as opportunities that can be utilized to enrich communication. This research uses a qualitative approach. The results of this study explain that the challenges of communication in the digital era are information overload, filter bubble, crisis of trust, data insecurity. Opportunities in the dynamics of digital communication are global reach, public participation, communication innovation and digital literacy development.

Decoding algorithmic literacy among journalists

Recent developments in generative Artificial Intelligence (AI) have revitalized academic discourse on algorithmic systems, particularly on their potential, ethical considerations, risks, and regulatory challenges. Extensive research has examined how algorithms affect communication processes, focusing on their influence on news organizations, journalistic practices, public-media dynamics, media literacy, and combating disinformation and filter bubbles. An emergent strand of research defines and measures the multidimensional concept of algorithmic literacy. However limited research exists on the intersection of algorithmic literacy and journalism. This gap is particularly concerning given the pivotal role of journalism in shaping public discourse, informing citizens, upholding democratic values and contrasting disinformation. Understanding how journalists perceive and engage with algorithms is essential, as these technologies significantly influence their professional tasks, including content production and distribution. In Portugal, where newcomer journalists work in precarious conditions and digital media transformation is rapidly evolving, understanding how journalists interact with and perceive algorithms is vital. Our study, through a multi-phased approach, aims to fill this gap questioning how can algorithmic literacy, encompassing cognitive, attitudinal and behavioural dimensions, be effectively assessed among professional journalists? The exploratory results present a validated methodological tool, instrument based on a multi-dimensional analytical framework and specifically designed to measure algorithmic literacy levels and to assess journalists’ experiences. Critical discussion addresses the methodological procedures and preliminary findings from the pre-test, offering insights into Portuguese journalists' understanding, perceptions, and competencies regarding algorithmic systems. By shedding light on the cognitive, affective, and behavioural aspects of journalists’ engagement with algorithms, this study contributes to a deeper understanding of the algorithmic literacy among journalists, which is essential to sustain the quality of their work and for an effective counteraction against disinformation. It also opens avenues for similar studies in other geographical or professional contexts.

The filter bubble generated by artificial intelligence algorithms and the network dynamics of collective polarization on YouTube: the case of South Korea

ABSTRACT This study examined the role of the ‘filter bubble,’ an algorithm-mediated YouTube video suggestion system, in political polarization and the presence of echo chamber patterns in public engagement. We examined the mechanism by which automated YouTube recommendations augment selective exposure to ideologically similar content and the network-based dynamics of collective polarization. We collected lists of videos recommended by conservative and progressive news media and the accompanying replies using YouTube application programming interfaces (APIs) embedded in YouTube Data Tools and Webometric Analyst 2.0. The study examined similarities in content of related videos and conversation networks between commenters, as well as the relationships between the videos, channels, and commenters. Almost half of the videos had content similar to the original videos offered by both conservative and progressive news media. The filter bubbles in progressive media were not as strong as those in conservative media. More than 30% of the videos recommended by progressive media were from legacy media, while this figure was 25% for conservative sources. This study has significant implications for reverse engineering studies because it collected data through APIs, which are neutral and can access YouTube servers without logging into individual IDs.

Rethinking the filter bubble? Developing a research agenda for the protective filter bubble

Filter bubbles and echo chambers have received global attention from scholars, media organizations, and the general public. Filter bubbles have primarily been regarded as intrinsically negative, and many studies have sought to minimize their influence. The detrimental influence of filter bubbles is well-studied. Filter bubbles may, for example, create information silos, amplify misinformation, and promote hatred and extremism. However, comparatively few studies have considered the other side of the filter bubble; its protective benefits, particularly to marginalized communities and those living in countries with low levels of press freedom. Through a review of the literature on digital safe spaces and protective filter bubbles, this commentary suggests that there may be a need to rethink the filter bubble, and it proposes several areas for future research.

Stop Talking about Echo Chambers and Filter Bubbles

AbstractIt is widely believed that we are facing a problem, even a crisis, caused by so‐called “echo chambers” and “filter bubbles.” Here, David Coady argues that this belief is mistaken. There is no such problem, and we should refrain from using these neologisms altogether. They serve no useful purpose, since there is nothing we can say with them that we cannot say equally well or better without them. Furthermore, they cause a variety of harms, including, ironically, a tendency to narrow public debate within predetermined limits.

Co-Activity Maximization in Online Social Networks

Social media with online social networks has risen to be a prevalent force in information diffusion and public discourse. Despite its popularity and convenience, social media has been criticized for contributing to societal and ideological polarization as the result of trapping users in an echo chamber and filter bubbles. An emerging line of research focuses on ways to redesign content or link recommendation algorithms to mitigate the polarization phenomenon. However, existing works mainly concentrate on node-level balancing, while omitting the balancing effect that can be incurred by edge interaction in social networks. In this article, we take the first step to study the problem (CoAM) that assuming two campaigns are present in a network, how we should select seeds for each so as to maximize the interaction/activity between the followers of two campaigns (co-activity) after the diffusion process is finished. We begin our analysis by showing the hardness of CoAM under two diffusion models that are generalized from wildly used diffusion models and its objective function is neither submodular nor supermodular. This encourages us to design a submodular function that acts as a lower bound to the objective, by exploiting which we are able to devise a greedy algorithm with a provable approximation guarantee. To overcome the #P-hardness of diffusion calculation, we further extend the notion of random reverse-reachable (RR) set to devise a scalable instantiation of our approximation algorithm. We experimentally demonstrate the quality of our approximation algorithm on datasets collected from real-world social networks.

Why Culture and Philosophy Matter for the Studies of Algorithmic Recommender Systems. An Example from the Time Prior to the Outbreak of the Russian–Ukrainian War in 2022

This study, conducted through 2020–2022, was an attempt to model a situation in which Russian-speaking users wanted to use YouTube to inform themselves about Crimea’s annexation, and who would then progress by watching videos relevant to the question, picking only relevant recommendations from the list of recommendations made by YouTube throughout the three stages of the experiment. The aim of the data collection was to explore filter bubbles, maintained by YouTube’s recommender algorithm, concerning this polarising issue. As a result, a network was detected which showed recommendations relevant to the topic and which was dominated by videos with positive evaluations of the Crimean annexation. A characteristic performance feature of this network is strong mutual relations, as they frequently related back to each other. As there are dependencies between the research design and the outcome, a conceptual discussion of methods in the field was included as well as the claim to broaden the perspective and to integrate the concepts of philosophy, sociology, and culture studies. In this regard, I follow Andreas Reckwitz’s understanding of the Web as ‘culture machine’ and adapt his notion of personalisation as singularisation as well as Elena Esposito's understanding of artificial communication between humans and algorithms.

Online bubbles and echo chambers as social systems

PurposeThe aim of the text is to reflect on the formation of the so-called digital echo chambers or filter bubbles, which are environments formed around particular topics whose objective is to promote a given political-ideological position. The argument the author puts forward is that echo chambers are social systems of interaction created to deal with the process of informational overload brought about by the consolidation of digital media in people’s daily lives.Design/methodology/approachThe author used Niklas Luhmann’s theory of social systems to explain what the author is calling social systems of interaction. Furthermore, the author made clarifications about: (1) the current debate regarding echo chambers; (2) what is the concept of “information” that the author is using to formulate the proposition and (3) what is the specificity that digital media bring when the author talks about informational overload and about the formation of echo chambers.FindingsThe author concluded that echo chambers can be seen as digital interaction systems, but the concept of “interaction” must be adapted. The author also concluded that echo chambers help society to deal with the phenomenon of informational overload.Originality/valueThere are few works which try to make a detailed analysis of echo chambers from a Luhmannian perspective. With the propositions presented in this text, along with other writings of the own, the author gives an important step in that direction by introducing the topic in the social systems researchers community.

Digital Media, Social Bubbles, Extremism and Challenges Implicated in the Construction of Identity and Respect for Diversity and Cultural Pluralism

The extensive use of digital platforms has presented considerable challenges to democracy, particularly in the realms of politics and ideology in Brazil. The emergence of digital echo chambers and the rise of extreme viewpoints pose threats to social cohesion, informed decision-making, and the development of individual identities. This analysis focuses specifically on identity formation, the creation and dissemination of information, emphasizing its repercussions on social identity and cultural diversity. Consequently, the influence of these echo chambers in promoting extremist views in this context is just one facet of the broader ideological, racial, and class polarization facing the nation. To face these challenges, it is imperative to defend critical and reflective education on the role and use of social networks, both in the educational system and in the daily lives of young people and society

Temporal clustering of social interactions trades-off disease spreading and knowledge diffusion.

Non-pharmaceutical measures such as preventive quarantines, remote working, school and workplace closures, lockdowns, etc. have shown effectiveness from an epidemic control perspective; however, they have also significant negative consequences on social life and relationships, work routines and community engagement. In particular, complex ideas, work and school collaborations, innovative discoveries and resilient norms formation and maintenance, which often require face-to-face interactions of two or more parties to be developed and synergically coordinated, are particularly affected. In this study, we propose an alternative hybrid solution that balances the slowdown of epidemic diffusion with the preservation of face-to-face interactions, that we test simulating a disease and a knowledge spreading simultaneously on a network of contacts. Our approach involves a two-step partitioning of the population. First, we tune the level of node clustering, creating 'social bubbles' with increased contacts within each bubble and fewer outside, while maintaining the average number of contacts in each network. Second, we tune the level of temporal clustering by pairing, for a certain time interval, nodes from specific social bubbles. Our results demonstrate that a hybrid approach can achieve better trade-offs between epidemic control and complex knowledge diffusion. The versatility of our model enables tuning and refining clustering levels to optimally achieve the desired trade-off, based on the potentially changing characteristics of a disease or knowledge diffusion process.

Freedom of choice and network "echo effects" of information consumption

The mechanisms of media personalization and separation in network communication on the principle of like-mindedness stimulate the formation of "echo chambers" and "filter bubbles". The social network phenomenon indicated by these metaphors is the subject of research, and the concepts themselves are considered as close, but not identical. The purpose of the study is to identify factors affecting the effectiveness of filtering algorithms, the user's ability to make informed choices and self–organization in the process of information consumption. The analysis of the causes and consequences of selective strategies of online information consumption is carried out on the basis of the communicative - activity approach, the theory of virtual reality Zh. Baudrillard, concepts of digital media by K. Sunstein, E. Pariser and R. Fletcher. The results of foreign and domestic studies of communication practices on various social platforms are used as an empirical basis. The research approaches presented in the scientific literature allow us to focus on the technological and logical-semantic perspective of the analysis of stable forms of network communication. According to the authors, the interdependence of filtering algorithms and value dominants of information consumption leaves the user with a chance to independently choose a "consumer basket". The duality in obtaining personalized content is emphasized: on the one hand, it is convenience, saving effort, on the other - the one-dimensionality of the world picture in the information bubble. Based on this, freedom of choice is characterized as the right to active choice and the right not to choose, consciously delegating it to neural network filters. In conclusion, the authors identified internal and external network factors for reducing the effectiveness of filtering algorithms: the interpretation of user behavior by artificial intelligence; the functioning of rational confrontational communication; the opportunistic conceptualization of echo effects; the availability of means of conscious counteraction. Incentives for reasonable information consumption, technological and cognitive ways of protecting and rationalizing user behavior are highlighted.

THE ROLE OF SOCIAL MEDIA ALGORITHMS IN SHAPING AND CONFLICT RESOLUTION

This research aims to explore the dual role of social media algorithms in conflict formation and resolution. Using a systematic literature review method, this research analyses how algorithms can amplify polarization and spread misinformation, as well as their potential to be leveraged in mitigating conflict and promoting constructive dialogue. The results show that algorithms designed to maximise user engagement often contribute to conflict escalation through the formation of "filter bubbles" and the spread of misinformation. However, recent research has also revealed the potential of algorithms, if designed with ethical and social principles in mind, to be instrumental in early conflict detection and the promotion of dialogue across groups. This study highlights the implications of these findings for technology companies, policymakers, and civil society, and emphasises the need for an interdisciplinary approach, proactive regulation, and increased digital literacy in addressing algorithm challenges. In conclusion, social media algorithms are flexible tools, and their impact depends on the values, principles, and goals embedded in their design. A holistic and collaborative approach is needed to harness the potential of algorithms in mitigating conflict while minimising their role in deepening social divisions.

Bubble reachers and uncivil discourse in polarized online public sphere.

Early optimism saw possibilities for social media to renew democratic discourse, marked by hopes for individuals from diverse backgrounds to find opportunities to learn from and interact with others different from themselves. This optimism quickly waned as social media seemed to breed ideological homophily marked by "filter bubbles" or "echo chambers." A typical response to the sense of fragmentation has been to encourage exposure to more cross-partisan sources of information. But do outlets that reach across partisan lines in fact generate more civil discourse? And does the civility of discourse hosted by such outlets vary depending on the political context in which they operate? To answer these questions, we identified bubble reachers, users who distribute content that reaches other users with diverse political opinions in recent presidential elections in Brazil, where populism has deep roots in the political culture, and Canada, where the political culture is comparatively moderate. Given that background, this research studies unexplored properties of content shared by bubble reachers, specifically the quality of conversations and comments it generates. We examine how ideologically neutral bubble reachers differ from ideologically partisan accounts in the level of uncivil discourse they provoke, and explore how this varies in the context of the two countries considered. Our results suggest that while ideologically neutral bubble reachers support less uncivil discourse in Canada, the opposite relationship holds in Brazil. Even non-political content by ideologically neutral bubble reachers elicits a considerable amount of uncivil discourse in Brazil. This indicates that bubble reaching and incivility are moderated by the national political context. Our results complicate the simple hypothesis of a universal impact of neutral bubble reachers across contexts.

Covid-19, identity, and piety online: ultra-Orthodox discussions in WhatsApp and Telegram groups under social distancing regulations

ABSTRACT The Covid-19 pandemic has disrupted relationships between religious communities and the state. Churches, religious authorities, and believers have been obligated to modify key activities (prayer, ceremonies) and weigh their religious identity against state prohibitions. Accordingly, we ask how members of a reclusive religious community negotiated and performed their identity under a prolonged emergency. We analyse intra-communal discourse concerning the state’s social distancing regulations during Covid-19 outbreaks and lockdowns that occurred in closed groups in messaging apps. Specifically, this research case-studies Jewish ultra-Orthodox communities in Israel (Haredim). Extensive analysis of over 2,000 WhatsApp and Telegram posts in 35 ultra-Orthodox groups over a two-year period indicates that participants constantly sought to affirm their primary, dominant, communal identity. While efforts to integrate adherence to state prohibitions into this primary identity were evident, these efforts were well accepted only when justifying them via affirmation of the communal identity – superseding medical, political, and practical concerns. The findings advance understanding of minority groups’ attitudes towards state directives and illuminate contemporary pathways of identity dynamics in online social networks. The findings may also be applicable in a broader sense to the study of discourse dynamics in echo chambers and filter bubbles.

Nudging Towards Responsible Recommendations: a Graph-Based Approach to Mitigate Belief Filter Bubbles

Nudging Towards Responsible Recommendations: a Graph-Based Approach to Mitigate Belief Filter Bubbles