Recommender systems on online platforms are often accused of polarizing user attention and consumption. The authors examine this phenomenon using a quasi-experiment conducted by Zhihu, the largest ...online knowledge-sharing platform (or Q&A community) in China. Zhihu originally used a content-based filtering algorithm, which recommends content to users on the basis of the topics to which each user has subscribed. After more than a year, Zhihu moved to a social filtering algorithm, which recommends content with which users’ social connections are already engaged. The authors find that this algorithm change increased the creation of social ties by approximately 15% but decreased question subscriptions by 20% and answer contributions by 23%. The authors show that users’ increased social interests mainly involved following popular users, leading to a greater concentration of social interests on the platform. However, users’ topical interests became less concentrated, as popular topics received significantly fewer subscribers than unpopular topics. The authors explain these findings by exploring the underlying mechanism. They show that compared with content-based filtering algorithms, social filtering algorithms are more likely to expose general users to content consumed by their followees, who are more interested in niche topics than general users are.
Online behavioral advertising is widely employed across the Internet. To mitigate the lack of transparency in tailored advertising and increase the acceptance of behavioral advertising, numerous ...platforms have adopted transparency measures by, for example, providing short explanations to users. We examine to what degree different levels of transparency, operationalized as degrees of detail, delivered through advertising explanations impact consumers' evaluations of behavioral targeted advertising and their trust in the platform presenting the ad. Empirically, we relied on an online experiment involving 174 Facebook users. Results showed that ad explanations with a medium level of detail led to more favorable advertising evaluations among users compared to ad explanations with a high level of detail.
The Facebook News Feed prioritizes posts for display by ranking them more prominently in the News Feed, based on users’ past interactions with the system. This study investigated constraints imposed ...on social interactions by the algorithm, by triggering participants’ awareness of “missed posts” in their Friends’ Timelines that they did not remember seeing before. If the algorithm prioritizes posts from people that users feel closer to and want to stay in touch with, participants should be less likely to report missed posts from close Friends. However, the results showed that relationship closeness had no effect on the likelihood of noticing a missed post, after controlling for how many Facebook Friends participants had and the accuracy of participants’ memories for their Friends’ Facebook activity. Also, missed posts from close Friends were more surprising, even when participants believed that the actions of the system caused the missed posts, indicating that these instances represent participants’ unmet expectations for the behavior of their News Feeds. Because Facebook posts present opportunities for feedback important for social support and maintaining social ties, this could indicate bias in the way the algorithm promotes content that could affect users’ ability to maintain relationships on Facebook. These findings have implications for approaches to improve user control and increase transparency in systems that use algorithmic filtering.
•The study examined how the Facebook News Feed algorithm constrains interaction.•Facebook users were prompted to notice posts from Friends that they had missed.•Relationship closeness did not affect the likelihood of noticing missed posts.•Missed posts from close Friends were more surprising, indicating unmet expectations.•Believing the algorithm caused missed posts was related to greater surprise.
Recommender systems are increasingly applied by traditional news organisations to structure and personalise their websites according to a set of predefined principles. But we have little insight into ...the people and processes involved in defining these principles and transforming them into code, despite their direct impact on online news selection and distribution. This article contributes to filling this research gap by investigating recommender system development and implementation at two Scandinavian news organisations. Drawing on field theory, the study explores the powerful position of developers and data scientists within news organisations and their working relationships around algorithmic curation. These new entrants into the field bring new forms of cultural capital and a performance-oriented doxa that clashes with the journalistic doxa, causing delays in the integration of the technology. The article highlights the important role of steering groups and bridging employees in balancing technical, commercial, and editorial concerns but also illuminates the lack of sustained collaboration between journalists and data scientists. Such overlapping and non-siloed collaboration can help build common ground and inter-field understanding and ease technology integration. To this end, the article suggests that long-term business objectives bridge the tech-editorial gap by bringing these different stakeholders together around a common goal.
•News algorithms affect the amount of substantive political news on Facebook.•The higher number of political news items on Facebook increases ideological concentration.•Reduction of ideological ...concentration operates through the “Law of Large Numbers” and a higher representation of niche ideologies.
Facebook has been criticized for exposing its users to low-quality and harmful information, including fake news, hate speech, and politically one-sided content. In December 2013 and again in August 2014, the platform updated its news feed algorithm to increase user exposure to quality content of news publishers, while curbing the proliferation of non-informative posts. This paper uses a sample of German newspapers to investigate the conjecture that these modifications raised the incentives to publish quality news stories on the platform, focusing on the number and diversity of news story posts about substantive political issues. Using the newspapers’ print editions as a counterfactual, our results indicate an increase in the amount of substantive political news on Facebook by approximately 30%. This expansion occurred in a politically balanced way, except that the outlets disproportionately increased their Facebook coverage of the formerly underrepresented Linke (Left Party). Consequently, the within-outlet concentration of political viewpoints decreased by about one half of the standard deviation of our concentration indices.
Search engines are important contemporary sources of information and contribute to shaping our beliefs about the world. Each time they are consulted, various algorithms filter and order content to ...show us relevant results for the inputted search query. Because these search engines are frequently and widely consulted, it is necessary to have a clear understanding of the distinctively epistemic role that these algorithms play in the background of our online experiences. To aid in such understanding, this paper argues that search engine algorithms are providers of “bent testimony”—that, within certain contexts of interactions, users act as if these algorithms provide us with testimony—and acquire or alter beliefs on that basis. Specifically, we treat search engine algorithms as if they were asserting as true the content ordered at the top of a search results page—which has interesting parallels with how we might treat an ordinary testifier. As such, existing discussions in the philosophy of testimony can help us better understand and, in turn, improve our interactions with search engines. By explicating the mechanisms by which we come to accept this “bent testimony,” our paper discusses methods to help us control our epistemic reliance on search engine algorithms and clarifies the normative expectations one ought to place on the search engines that deploy these algorithms.
"Am I Never Going to Be Free of All This Crap?" Pinter, Anthony T.; Jiang, Jialun Aaron; Gach, Katie Z. ...
Proceedings of the ACM on human-computer interaction,
11/2019, Letnik:
3, Številka:
CSCW
Journal Article
Recenzirano
Every day on social media, people see streams of content curated by algorithms that leverage their relationships, preferences, and identities. However, algorithms can oversimplify the complexity of ...people's social contexts. Consequently, algorithms can present content to people in ways that are insensitive to their circumstances. Through 19 in-depth interviews, our empirical study examines instances of contextually insensitive content through the lens of people's upsetting encounters with content about their ex-romantic partners on Facebook. We characterize the encounters our participants had with content about their exes, including where on Facebook it occurred, the types of social connections involved in the content, and participants' perceptions of why the content appeared. Based on our findings, we describe the "social periphery"---the complex social networks and data that enable inferred connections around otherwise explicit relationships---and discuss the design challenges that the periphery presents designers.
Considering the implications of cross-cutting exposure for democratic deliberation in the age of algorithms, this study proposes a conceptual model that delineates the roles of perceived realism and ...approval of algorithmic curation in the relationship between cross-cutting exposure and online political engagement. Secondary data obtained from the 2018 national survey conducted by the Taiwan Institute for Governance and Communication Research were utilized to test the relationships. The results indicated a negative association between cross-cutting exposure and online political engagement. The significant mediation model further showed that exposure to cross-cutting perspectives on social media was negatively associated with online political engagement by way of decreased perceived realism. That association was conditioned by the level of approval of algorithmic curation, which weakened the negative mediating role of perceived realism as it increased. Implications of those results and directions for future research are discussed.
Facebook users are exposed to diverse news and political content; this means that Facebook is a significant tool for the enhancement of civic participation and engagement in politics. However, it has ...been argued that Facebook, through its algorithmic curation reinforces the pre-existing attitudes of individuals, rather than challenging or potentially altering them. The objective of this study is to elucidate the emotional and behavioural impact of the personalization of Facebook users’ News Feeds results, and thereby to uncover a possible link between their online and offline civic attitudes. Firstly, we investigate the extent to which users’ Facebook News Feeds results are personalized and customized to fit users’ pre-existing civic attitudes and political interests. Secondly, we explore whether users embody new roles as a result of their emotional and behavioural interaction with political content on Facebook. Our methodology is based on a quantitative survey involving 108 participants. Our findings indicate that, while Facebook can potentially expose users to varying political views and beliefs, it tends to reinforce existing civic attitudes and validate what users already hold to be true. Furthermore, we find that users themselves often assume a proactive stance towards Facebook News Feed results, acquiring roles in which they filter and even censor the content to which they are exposed and thus trying to obfuscate algorithmic curation.
Amid the widespread diffusion of digital communication technologies, our cities are at a critical juncture as these technologies are entering all aspects of urban life. Data-driven technologies help ...citizens to navigate the city, find friends, or discover new places. While these technology-mediated activities come in scope of scholarly research, we lack an understanding of the underlying curation mechanisms that select and present the particular information citizens are exposed to. Nevertheless, such an understanding is crucial to deal with the risk of the socio-cultural polarization assumedly reinforced by this kind of algorithmic curation. Drawing upon the vast amount of work on algorithmic curation in online platforms, we construct an analytical lens that is applied to the urban environment to establish an understanding of algorithmic curation of urban experiences. In this way, this article demonstrates that cities could be considered as a new materiality of curational platforms. Our framework outlines the various urban information flows, curation logics, and stakeholders involved. This work contributes to the current state of the art by bridging the gap between online and offline algorithmic curation and by providing a novel conceptual framework to study this timely topic.
PDF
