Article
Computer Science, Cybernetics
Seung Yeop Lee, Sang Woo Lee
Summary: This study examines the impact of personalized recommendations on news usage intention and finds that perceived personalization has a positive effect on continuance intention through the mediation of trust, user satisfaction, and perceived usefulness. Additionally, perceived news diversity also has a positive effect on continuance intention through the mediation of user satisfaction.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
(2023)
Article
Computer Science, Interdisciplinary Applications
Katharina Ludwig, Alexander Grote, Andreea Iana, Mehwish Alam, Heiko Paulheim, Harald Sack, Christof Weinhardt, Philipp Mueller
Summary: Recent increases in political polarization are often attributed to algorithmic content filtering on social media, news platforms, or search engines. News recommendation systems (NRS) are widely used and are believed to contribute to affective, ideological, and perceived polarization by creating homogenous information environments. In an online experiment with 750 participants, we tested this assumption by enriching a content-based NRS with negative or neutral sentiment. The findings show limited evidence for polarization effects of content-based NRS, but indicate that the time spent on the system and its recommended articles play a crucial role in moderating polarization. Participants who spent more time with an NRS enriched with negative sentiment became more affectively polarized, while those using a NRS incorporating balanced sentiment experienced ideological depolarization over time. Implications for future research are discussed.
SOCIAL SCIENCE COMPUTER REVIEW
(2023)
Article
Multidisciplinary Sciences
Ronald E. Robertson, Jon Green, Damian J. Ruck, Katherine Ognyanova, Christo Wilson, David Lazer
Summary: If popular online platforms systematically expose their users to partisan and unreliable news, it could lead to societal issues such as increased political polarization. The 'echo chamber' and 'filter bubble' debates criticize how user choice and algorithmic curation guide individuals to different online sources of information. This study aimed to address the gaps in research by conducting a two-wave study that measured exposure and engagement on Google Search during the 2018 and 2020 US elections. The findings suggest that users' own choices, rather than algorithmic curation, drive exposure to and engagement with partisan or unreliable news on Google Search.
Article
Communication
Roan Schellingerhout, Davide Beraldo, Maarten Marx
Summary: This article investigates the conditions under which YouTube's recommender system tends to favor conspiracy-classified videos. The study focuses on the personalization and diversified user strategies, rather than non-personalized recommendations and standard watch patterns. Authenticated bots were used to watch YouTube content based on different watch strategies, and the impact on the proportion of conspiracy-classified content recommended was measured. The results show that users exposed to conspiracy-classified content quickly receive more recommendations for similar content, and personalized content input may have a stronger effect.
DIGITAL JOURNALISM
(2023)
Article
Communication
Anna Schjott Hansen, Jannie Moller Hartley
Summary: This article presents the results of an ethnographic study on the development of a personalization algorithm in a Danish news organization. The study shows how the algorithm changes the distribution of news from segments of consuming collectives to aggregated data points of individual users. It also explores the negotiations and risks involved in this transformation.
DIGITAL JOURNALISM
(2023)
Article
Computer Science, Interdisciplinary Applications
Roberto Ulloa, Mykola Makhortykh, Aleksandra Urman, Juhi Kulshrestha
Summary: The news coverage of the 2020 US elections was extensive, with new information being generated rapidly. This provided an opportunity to study the performance of search engines in quickly processing and presenting this information. The researchers conducted a longitudinal study comparing the coverage and visibility of different topics by analyzing the novelty of the search results. They found that election-related queries produced more new items compared to other topics, and demonstrated that their method could capture sudden changes in highly covered news topics as well as differences across search engines and regions.
SOCIAL SCIENCE COMPUTER REVIEW
(2023)
Article
Automation & Control Systems
Suman Yadav, Richa Yadav, Ashwni Kumar, Manjeet Kumar
Summary: The study utilized a grasshopper optimization algorithm to design digital filters and compute optimal filter coefficients to achieve the desired objectives. An absolute error difference fitness function was used for the design of the FIR filter, minimizing errors for optimal coefficients. Performance comparison with existing algorithms showed the superiority of the proposed GOA-based filter design.
Article
Communication
Lawrence Van den Bogaert, David Geerts, Jaron Harambam
Summary: This article explores the concept of algorithmic recommender personae as a potential solution to the lack of transparency, diversity, and agency in recommender systems. Through qualitative research, the researchers identified three distinct recommender personae types that align with news consumers' main reading motivations. The results highlight the importance of giving users more control and involving them in the design of recommender systems in an increasingly automated future.
DIGITAL JOURNALISM
(2022)
Article
Geochemistry & Geophysics
Yichen Li, Gang Liu, Zongwen Jia, Min Qin, Gang Wang, Yinan Hu, Jialin He, Kai Wang
Summary: Sand production is a common problem in unconventional oil and gas exploitation, and accurate online monitoring of sand production is crucial for ensuring the safety and efficiency of oil wells. This paper presents a method for monitoring sand production in offshore oil wells based on vibration response characteristics, which has been validated through field tests.
Article
Communication
Richard Fletcher, Antonis Kalogeropoulos, Rasmus Kleis Nielsen
Summary: The rise of new, distributed forms of news access has shaped people's news use, leading to more diverse news repertoires. However, it is also associated with a higher prominence of partisan outlets.
NEW MEDIA & SOCIETY
(2023)
Article
Communication
Patrick F. A. van Erkel, Peter Van Aelst
Summary: This study finds that citizens do not gain more political knowledge from following news on social media compared to traditional media channels, and there is even a negative association between following news on Facebook and political knowledge. The research suggests that information overload on social media decreases what people actually learn, especially for those who combine social media news with other news sources.
POLITICAL COMMUNICATION
(2021)
Article
Thermodynamics
Shawn Siroka, Reid A. Berdanier, Karen A. Thole
Summary: This research extends the solutions to the inverse heat conduction problem (IHCP) using an impulse response methodology, which allows quantification of surface heat flux in multi-layer materials for components with limited subsurface temperature measurements. Comparing the impulse method to the inverse method, the impulse method exhibits lower errors in calculating surface heat flux across various conditions, providing a foundation for deducing subsurface heat flux while maintaining a high-frequency response.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2022)
Article
Computer Science, Information Systems
Chuhan Wu, Fangzhao Wu, Yongfeng Huang, Xing Xie
Summary: Personalized news recommendation is crucial for users to find interesting news information and alleviate information overload. This article provides a comprehensive overview of personalized news recommendation, including techniques for addressing core problems, challenges, public datasets, evaluation methods, and ways to improve the responsiveness of recommender systems. It also suggests future research directions.
ACM TRANSACTIONS ON INFORMATION SYSTEMS
(2023)
Article
Communication
Victor Wiard, Brieuc Lits, Marie Dufrasne
Summary: This paper presents a study on how social media platforms influence young adults' opinion formation through content personalization. It problematizes the filter bubble phenomenon and proposes a theoretical framework of Activity Theory for understanding the diversity of practices and discourses regarding access to content and news. The methods used to gather data and the results, which show young people's understanding of content recommendation mechanisms, are discussed.
FRONTIERS IN COMMUNICATION
(2022)
Article
Computer Science, Artificial Intelligence
Nabila Amir, Fouzia Jabeen, Zafar Ali, Irfan Ullah, Asim Ullah Jan, Pavlos Kefalas
Summary: This survey fills the gap in the literature by summarizing the strengths, weaknesses, and trends of news recommendation models employing DL methods. It also discusses the commonly used datasets, evaluation methods, and implications for researchers in this area.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Computer Science, Interdisciplinary Applications
Aleksandra Urman, Mykola Makhortykh, Roberto Ulloa
Summary: The study reveals substantial differences in search results among different search engines under non-personalized conditions, as well as discrepancies within results generated for different agents. The randomization of search results determines if users see certain information, and some search engines prioritize different categories of information sources for specific candidates.
SOCIAL SCIENCE COMPUTER REVIEW
(2022)
Article
Communication
Marielle Wijermars
Summary: This article examines how the Russian government justifies and garners popular support for restricting online freedoms, with a focus on the case of Telegram being banned in 2018. The study found that media framing of the ban was more diverse than the official governmental line, with the 'rule of law' frame occurring most frequently.
INFORMATION COMMUNICATION & SOCIETY
(2022)
Article
Communication
Olga Dovbysh, Marielle Wijermars, Mykola Makhortykh
Summary: Technological corporations and digital services are increasingly influential in news production and dissemination, particularly through the use of algorithmic recommender systems. This article investigates the relationship between Russian media outlets and Yandex, focusing on the personalized content recommendation platform Yandex.Zen and its content prioritization program Nirvana. It explores how power dynamics within the recommender system's multi-stakeholder environment affect journalistic practices.
DIGITAL JOURNALISM
(2022)
Article
Computer Science, Information Systems
Roberto Ulloa, Mykola Makhortykh, Aleksandra Urman
Summary: This article discusses the challenges, methodological details, recommendations, lessons learned, and limitations of using virtual agents for algorithm audits. It demonstrates successful experiences in setting up experiments for different search engines and multiple data collections, highlighting changes and strategies to improve method quality.
JOURNAL OF INFORMATION SCIENCE
(2022)
Article
Communication
Marielle Wijermars, Mykola Makhortykh
Summary: The use of datafication and algorithmic systems blurs boundaries between policy fields, as seen in the European Union's different sociotechnical imaginaries of algorithmic governance in online disinformation and FinTech.
NEW MEDIA & SOCIETY
(2022)
Article
Communication
Mykola Makhortykh, Aleksandra Urman, Felix Victor Muench, Amelie Heldt, Stephan Dreyer, Matthias C. Kettemann
Summary: The growth of online platforms has led to the increasing use of automated agents. While primarily discussed in the context of opinion manipulation, agents play diverse roles within platform ecosystems, necessitating governance approaches that go beyond monitoring agents' undesirable behavior. To provide a more comprehensive understanding of agent governance, an analytical framework is introduced to differentiate between different aspects and forms of governance. This framework is then applied to examine the governance of agents across nine platforms. The findings show that while platforms acknowledge the various roles of agents, they tend to focus on governing specific forms of misuse. Variations in governance approaches, particularly concerning agent rights/obligations and transparency of policing mechanisms, are also observed. These observations underscore the need for advancing research on algorithmic governance and developing a generalizable normative framework for agent governance.
NEW MEDIA & SOCIETY
(2022)
Article
Communication
Juan Manuel Gonzalez-Aguilar, Mykola Makhortykh
Summary: The rise of user-generated content presents both positive and negative impacts on the mediatization of historical memory. Internet memes have various functions, including trivializing Holocaust memory, reinforcing canonical narratives, and depending on other forms of memory mediatization.
MEDIA CULTURE & SOCIETY
(2022)
Article
Communication
Ernesto de Leon, Mykola Makhortykh, Teresa Gil-Lopez, Aleksandra Urman, Silke Adam
Summary: This study examines the changes in political trust during the COVID-19 pandemic outbreak in Switzerland and investigates the roles of media consumption and threat perceptions in individuals' trust in politics. The findings reveal that political trust increased following the lockdown, while consumption of mainstream news on COVID-19 hindered this increase. Moreover, threat perceptions to health and government policy response had opposite effects on political trust, and these perceptions also moderated the impact of COVID-19 news consumption on government trust.
INTERNATIONAL JOURNAL OF PRESS-POLITICS
(2023)
Article
Communication
Silke Adam, Aleksandra Urman, Dorothee Arlt, Teresa Gil-Lopez, Mykola Makhortykh, Michaela Maier
Summary: We analyzed short-term changes in media trust during the COVID-19 pandemic in German-speaking Switzerland, focusing on its ideological drivers and consequences. Our findings highlight the significance of media trust in influencing people's willingness to comply with COVID-19 regulations. Media trust levels decreased for most media outlets during the pandemic, with the exception of public service broadcasting. Unlike the United States, Switzerland did not experience a partisan trust divide.
COMMUNICATION RESEARCH
(2023)
Article
Communication
Juan Manuel Gonzalez-Aguilar, Francisco Segado-Boj, Mykola Makhortykh
Summary: This article examines the strategies used by right-wing populist parties and politicians on TikTok, focusing on the presence of hate speech and entertaining features in their videos. The study finds that Vox and UKIP use TikTok to convey their ideology and target the state as the enemy, while Kast utilizes the platform to build his leadership image and share humorous content. Only 19% of the analyzed videos include hate speech, which not only is uncommon but also deters user engagement. In contrast, humor and entertainment enhance user engagement. The study suggests that TikTok may downplay the most controversial issues of right-wing populism.
MEDIA AND COMMUNICATION
(2023)
Article
Communication
Tetyana Lokot, Marielle Wijermars
Summary: International rankings have a significant impact on defining and highlighting the issues they aim to capture. In the past two decades, the proliferation of indexes measuring internet freedom worldwide has increased due to the expansion of internet access. This article examines the politics behind these rankings, which have become influential in shaping the understanding of internet freedom and serving as tools of political or diplomatic influence.
INTERNET POLICY REVIEW
(2023)
Article
Communication
Michael Tschirky, Mykola Makhortykh
Summary: Social media platforms play a crucial role in shaping public perception of contemporary wars, including the ongoing Russian invasion of Ukraine. However, studying how these platforms represent violence and the aspects that users emphasize presents multiple challenges. The authors compare qualitative content analysis and topic modeling to investigate the framing of the siege of Mariupol in 2022 on Twitter during the Russian-Ukrainian war. Their findings reveal similarities in the prevalence of human interest and conflict frames, consistent with previous research, but also identify differences in the visibility of less common frames such as morality and responsibility, depending on the method used.
MEDIA WAR AND CONFLICT
(2023)
Article
Communication
Mykola Makhortykh, Mariella Bastian
Summary: The use of algorithmically tailored individual news feeds is seen as an important strategy for legacy media to meet consumers' information needs. However, this personalization of news distribution raises concerns about the societal function of legacy media, especially when dealing with traumatic and divisive content. This article provides a conceptual assessment of adopting personalization for conflict coverage in Ukraine and Russia, where press freedom is limited.
MEDIA WAR AND CONFLICT
(2022)
Article
Communication
Mykola Makhortykh, Maryna Sydorova
Summary: This article discusses the interaction between digital greeting cards and hegemonic historical narratives in war remembrance contexts. It uses Foucault's concept of counter-memory to analyze the interaction between user-generated mnemonic content and historical power relations. Through content analysis of amateur greeting cards, the authors investigate how these cultural products engage with official and counter-official memory practices in Russia related to the Soviet victory in the Second World War. The article explores how different visual elements are used to (de)construct specific narratives about the Soviet victory and discusses how the use of computer graphics, particularly animation, influences the potential role of greeting cards in resurrecting the suppressed past.
VISUAL COMMUNICATION
(2022)
