Reducing the filter bubble effect on Twitter by considering communities for recommendations

Purpose Social network platforms are considered today as a major communication mean. Their success leads to an unprecedented growth of user-generated content; therefore, finding interesting content for a given user has become a major issue. Recommender systems allow these platforms to personalize individual experience and increase user engagement by filtering messages according to user interest and/or neighborhood. Recent research results show, however, that this content personalization might increase the echo chamber effect and create filter bubbles that restrain the diversity of opinions regarding the recommended content. Design/methodology/approach The purpose of this paper is to present a thorough study of communities on a large Twitter data set that quantifies the effect of recommender systems on users’ behavior by creating filter bubbles. The authors further propose their community-aware model (CAM) that counters the impact of different recommender systems on information consumption. Findings The authors propose their CAM that counters the impact of different recommender systems on information consumption. The study results show that filter bubbles effects concern up to 10% of users and the proposed model based on the similarities between communities enhance recommendations. Originality/value The authors proposed the CAM approach, which relies on similarities between communities to re-rank lists of recommendations to weaken the filter bubble effect for these users.

Algorithmic personalization of source cues in the filter bubble: Self-esteem and self-construal impact information exposure

How do users pick out online information sources? Building on a self-regulation perspective to media use, this study investigates routes to self-enhancement (i.e. state self-esteem [SSE] increase) through selective exposure to sources of political online information. Personal-self importance (PSI) and social-self importance (SSI) were conceptualized as moderators of self-enhancement. An experiment mimicked the filter bubble, as participants ( n = 88) browsed only attitude-aligned political content. The experiment varied source cues, with two (of eight) bylines displaying individual participants’ name initials as author initials. The selective exposure time participants spent on messages from same-initials authors was logged to capture egotism (based on the well-established name-letter effect). Pre-exposure SSE influenced self-enhancement, contingent upon both PSI and SSI. Perceived source similarity affected post-exposure SSE, contingent upon the same moderators. The findings show that algorithms can personalize source cues to attract users and impact self-esteem.

An Empirical Study on Filter Bubbles in the YouTube Comments Network

Some point out that the influence of YouTube's video recommendation algorithm is causing users to be exposed to only video clips in limited subjects or fields, especially to biased content with opinions that are tilted to one side. However, there is a lack of empirical research on filter bubbles as algorithms in YouTube have not been disclosed. This study indirectly demonstrated the phenomenon of filter bubble on YouTube by extracting comment-based content network between uploaders who posted videos and writers who wrote comments on the video by each subject of the contents. Also, this study analyzed communication patterns between users through social network analysis (SNA). According to the analysis, users' narrow information acquisition and communication phenomenon caused by the filter bubble in YouTube was found.

DISINFORMATION DECONSTRUCTEDCOGNITION SECURITY AND DIGITAL CONTROL

Fake News and Deepfakes have lately been highlighted in informative videos, research papers and literature reviews as tools for disinformation, along with filter bubble and echo chamber, polarization and mistrust. To counteract the unconventional weapons of word and imagery, a new research area has been defined as cognition security, a transdisciplinary area to understand the threats hybrid wars currently make use of and to determine the proper measures against non-kinetic offensives. For this, data mining and deep analysis are performed with digital instruments in a cognitive security system. Defined by all these, the present paper deconstructs the terms in an experimental monitoring of the media, to connect the realm of Cognition Security to its instruments in Cognitive Security Key words: Fake news, deepfake, cognitive security, narrat

Pengaruh algoritma filter bubble dan echo chamber terhadap perilaku penggunaan internet

Introduction. This study aims to explore effects of bubble filter and echo chamber on information searching behaviour on the internet, how it affects the scope of the internet ecosystem and users, and what we can see from the behaviour. Data Collection Method. The paper used a mixed-methods approach with surveys, online discussions, and literature research. Twenty respondents between 19-21 years old participated in this exploratory study. Analysis Data. Data was obtained and calculations have automatically accumulated through Google Form. The user data analysis and discussion were conducted manually by considering aspects of rationality concerning the literature and previous research. Results and Discussions. The analysis results obtained were bubble filter and echo chambers were proven to affect internet users both in positive and negative ways. Conclusions. Bubble filter and echo chamber may have both positive and negative effects simultaneously, however, it depends on the user because the system has provided control features to reduce both features. Using internet wisely is also parts of the important aspect.

Political Polarization and Selective Exposure of Social Media Users in Indonesia

This study is intended to answer the question of how political polarization is related to social media users’ posts about Covid-19. The researchers chose health cases related to Covid-19 instead of political issues (e.g. elections) to prove that this political polarization has spread to many areas. The research also wants to see the relationship between this political polarization and selective exposure. Theories applied in this study are polarization, filter bubble, and selective exposure. The study applied two methods: social media network analysis and content analysis. The network analysis included 82,156 posts, while the content analysis was carried out on 4,050 social media accounts. The research outcome proves the occurrence of political polarization. Social media users were divided into two major groups, namely pro-Jokowi and anti-Jokowi. Each group interacted with fellow users who had the same political choices and shared the same message content. Users with certain political choices tend to receive the same information as their political choices, and ignore information from other political parties. Another interesting finding from this study is how this polarization was sharpened by the use of hashtags. Each party (supporters and oppositions of Jokowi) uses hashtags to create solidarity and mobilization from each supporter. Research also proves the validity of the selective exposure and filter bubble hypothesis in the Indonesian context.

Use of post-truth as a political tool

This paper shows, through the analysis of the literature and the most recent news, how through the use of neural algorithms and the application of strategies framed in what is called post-truth, certain political groups, mainly those who hold power in democracies with weak institutions, create a segmented reality that serves their interests and that in turn makes the task of exposing the factual facts more complicated.methodologies as long as appropriate teacher training and education processes are in place. Keywords: Post-truth, discrete reality, politics. References [1]P. Berger y T. Luckmann, Construcción social de la realidad, Buenos Aires: Amorrortu Editores, 2003. [2]F. B. Morales Romero y R. R. Martínez Martínez, «La posverdad: identidades colectivas que degeneran las democracias,» Anagramas Rumbos y Sentidos de la Comunicación, vol. 19, nº 37, pp. 111-126, 2020. [3]M. Barón Pulido, Á. Duque Soto, F. Mendoza Lozano y Q.P. Wilmer, «Redes sociales y relaciones digitales, una comunicación que supera el cara a cara,» Revista Internacional de Pedagogía en Innovación educativa, vol. 1, nº 1, pp. 123-148, 2020. [4]P. Iosifidis, «The battle to end fakenews: A qualitative content analysis of Facebook announcements on how it combats disinformation,» The International Communication Gazette, vol. 82, nº 1, pp. 60-81, 2020. [5]D. Kaufman y L. Santaella, «The role of artificial intelligence algorithms in the social web,» Revista Famecos- Midia, Cultura e Tecnologia, vol. 2020, nº Unique, pp. 20-26, 2020. [6]J. Habermas, Historía y crítica de la opinión pública, Barcelona: Gustavo Gili, 2002. [7]E. Noelle-Neumann, La espiral del silencio, Barcelona:Paidós, 2010. [8]D. Innerarity, Politica para perplejos, Barcelona: Galaxia Gutenberg, 2018. [9]I. Blanco Alfonso, «Posverdad, percepción de la realidad y opinión pública. Una aproximación desde la fenomenología, » Revista de Estudios Políticos, 187, vol. 2020, nº 187, pp. 167-186, 2020. [10]V. Bufacchi, «Truth, lies and tweets: A Consensus Theory of Post-Truth.,» Philosophy and Social Criticism, vol. 47, nº3, p. 347–361, 2021. [11]J. Ortega y Gasset, Meditaciones del Quijote, Madrid: Espasa-Calpe, 1969. [12]c. Belvedere, «El problema de la realidad en el marco de la influencia hispánica en la obra de Alfred Schutz,» Investigaciones Fenomenológicas, vol. 4, nº II, pp. 245-277, 2013. [13]A. Schutz, El problema de la realidad social, Buenos Aires: Amorrortu Editores, 1995. [14]Y. Hernández Romero y R. V. Galindo Sosa, «El concepto de intersubjetividad en Alfred Schutz,» espacios Públicos, vol. 10, nº 20, pp. 228-240, 2007. [15]L. Aguilar Villanueva, «Una reconstrucción del concepto de opinión pública,» Revista Mexicana de opinión pública, vol. 12, nº 23, pp. 125-148, 2017. [16]Wikipedia, «es.wikipedia.org,» Wikipedia, 27 March 2021. [En línea]. Available: https://es.wikipedia.org/wiki/Gallup_(empresa). [Último acceso: 30 March 2021]. [17]W. Lippmann, La opinión público, Madrid: Cuadernos de Langre, 2003. [18]P. Capilla, «De qué hablamos cuando hablamos de posverdad? Análisis del término en siete diarios de calidad.,» ElProfesional de la Información , vol. 28, nº 3, pp. 1-12, 2019. [19]D. Peter, «Public Sphere Participation Online: the Ambiguities of Affect,» Dans Les Enjeux de l'information et de la communication , vol. 19, nº 1, pp. 5-20, 2019. [20]I. Schulze Schneider, «Los medios de comunicación en la Gran Guerra: Todo por la Patria,» Historia y Comunicación Social, vol. 18, nº 1, pp. 15-30, 2013. [21]E. Parisier, The Filter Bubble: What The Internet Is Hiding From, New York: Penguin, 2012. [22]TED, «www.ted.com,» TED, 1 March 2011. [En línea]. Available: https://www.ted.com/talks/eli_pariser_beware_online_filter_bubbles?language=es. [Último acceso: 25 January 2021]. [23]B.-C. Han, La sociedad de la transparencia, Barcelona: Herder, 2013. [24]J. A. O. y. Romero, «Desinformación: concepto y perspectivas,» Real Instituto Elcano, vol. 2019, nº 41, pp. 1-8, 2019. [25]M. Arias Maldonado, La democracia sentimental. politica y emociones del siglo XXI, Barcelona: Página Indómita, 2016. [26]S. Tesich, «A government of lies,» The Nation, p. Online, 6 January 1992. [27]d. Innerarity y C. Colomina, «La verdad en las democracias algorítmicas,» Revista CIDOB d’Afers Internacionals, vol. 2020, nº 124, pp. 11-23, 2020. [28]E. Herreras y M. García-Granero, «Sobre verdad, mentira y posverdad. Elementos para una filosofía de la información., » Bajo Palabra, vol. 2020, nº 24, pp. 157-176, 2020. [29]C. Iriarte, «La era de la inmediatez,» Milenio, p. online, 28 February 2017. [30]J. E. García-Guerrero, «Redes sociales e interés político, » Icono 14, vol. 17, nº 2, pp. 231-253, 2018. [31]A. M. Lorusso, «Between Truth, Legitimacy, and Legality in the Post truth,» International Journal Semiot law, vol. 2020, nº 33, pp. 1005-1017, 2020. [32]K. Amer y J. Noujaim, Dirección, The great hack. [Película]. EEUU: netflix, 2019. [33]R. Trejo, «Escepticismo democrático y medios en disputa en tiempos de la posverdad,» Revista de la asociación española de investigaci{on de la comunicación, vol. 4, nº 8, pp. 2-9, 2017.