The internet has become a popular resource to learn about health and to investigate one's own health condition. However, given the large amount of inaccurate information online, people can easily ...become misinformed. Individuals have always obtained information from outside the formal health care system, so how has the internet changed people's engagement with health information? This review explores how individuals interact with health misinformation online, whether it be through search, user-generated content, or mobile apps. We discuss whether personal access to information is helping or hindering health outcomes and how the perceived trustworthiness of the institutions communicating health has changed over time. To conclude, we propose several constructive strategies for improving the online information ecosystem. Misinformation concerning health has particularly severe consequences with regard to people's quality of life and even their risk of mortality; therefore, understanding it within today's modern context is an extremely important task.
The science of fake news Lazer, David M J; Baum, Matthew A; Benkler, Yochai ...
Science (American Association for the Advancement of Science),
03/2018, Letnik:
359, Številka:
6380
Journal Article
Recenzirano
Addressing fake news requires a multidisciplinary effort
The rise of fake news highlights the erosion of long-standing institutional bulwarks against misinformation in the internet age. Concern over ...the problem is global. However, much remains unknown regarding the vulnerabilities of individuals, institutions, and society to manipulations by malicious actors. A new system of safeguards is needed. Below, we discuss extant social and computer science research regarding belief in fake news and the mechanisms by which it spreads. Fake news has a long history, but we focus on unanswered scientific questions raised by the proliferation of its most recent, politically oriented incarnation. Beyond selected references in the text, suggested further reading can be found in the supplementary materials.
The Parable of Google Flu: Traps in Big Data Analysis Lazer, David; Kennedy, Ryan; King, Gary ...
Science (American Association for the Advancement of Science),
03/2014, Letnik:
343, Številka:
6176
Journal Article
Recenzirano
Odprti dostop
Large errors in flu prediction were largely avoidable, which offers lessons for the use of big data.
In February 2013, Google Flu Trends (GFT) made headlines but not for a reason that Google ...executives or the creators of the flu tracking system would have hoped.
Nature
reported that GFT was predicting more than double the proportion of doctor visits for influenza-like illness (ILI) than the Centers for Disease Control and Prevention (CDC), which bases its estimates on surveillance reports from laboratories across the United States (
1
,
2
). This happened despite the fact that GFT was built to predict CDC reports. Given that GFT is often held up as an exemplary use of big data (
3
,
4
), what lessons can we draw from this error?
Abstract
Peers influence students’ academic decisions and outcomes. For example, several studies with strong claims to causality demonstrate that peers affect the choice of and persistence in majors. ...One remaining issue, however, has stymied efforts to translate this evidence into actionable interventions: the literature has not grappled adequately with the fact that in natural settings, students typically select most of their peers. The bulk of causal evidence for peer influence comes from exogenously assigned peers (e.g., roommates) because peer effects are easier to identify in such cases. However, students do not form their most important ties for the convenience of scientific inference. In order to link theory and practice, we need to understand which peers are influential. We employ longitudinal, multiplex network data on students’ choices of and persistence in their majors from 1260 students across 14 universities to identify likely causal pathways of peer influence via self-selected peers. We introduce time-reversed analysis as a novel tool for addressing some selection concerns in network influence studies. We find that peers with whom a student reports merely spending time, rather than—e.g., close friends, study partners, esteemed peers—consistently and potently influence their college major choice.
What are the relational dimensions of politics? Does the way that people and organizations are connected to each other matter? Are our opinions affected by the people with whom we talk? Are ...legislators affected by lobbyists? Is the capacity of social movements to mobilize affected by the structure of societal networks? Powerful evidence in the literature answers each of these questions in the affirmative. However, compared to other paradigmatic foci, political science has invested tiny amounts of capacity in the study of the relevance of networks to political phenomena. Far more attention has been paid to the psychology of how people process information individually as opposed to collectively, and to the role that institutions play in structuring politics as opposed to the relational undergirdings of politics. A review of the flagship journals in political science reveals a dearth of articles on networks. Few, if any, doctoral programs include courses for which the primary focus is network-related ideas, and even the notion of a relational dependence in data is rarely mentioned in discussions of the assumptions embedded in the statistical methods that dominate political science.
Whether as team members brainstorming or cultures experimenting with new technologies, problem solvers communicate and share ideas. This paper examines how the structure of communication networks ...among actors can affect system-level performance. We present an agent-based computer simulation model of information sharing in which the less successful emulate the more successful. Results suggest that when agents are dealing with a complex problem, the more efficient the network at disseminating information, the better the short-run but the lower the long-run performance of the system. The dynamic underlying this result is that an inefficient network maintains diversity in the system and is thus better for exploration than an efficient network, supporting a more thorough search for solutions in the long run. For intermediate time frames, there is an inverted-U relationship between connectedness and performance, in which both poorly and well-connected systems perform badly, and moderately connected systems perform best. This curvilinear relationship between connectivity and group performance can be seen in several diverse instances of organizational and social behavior.
Diversity tends to generate more and better ideas in social settings, ranging in scale from small-deliberative groups to tech-clusters and cities. Implicit in this research is that there are ...knowledge-generating benefits from diversity that comes from mixing different individuals, ideas, and perspectives. Here, we utilize agent-based modeling to examine the emergent outcomes resulting from the manipulation of how diversity is distributed and how knowledge is generated within communicative social structures. In the context of problem solving, we focus on cognitive diversity and its two forms: ability and knowledge. For diversity of ability, we find that local diversity (intermixing of different agents) performs best at all time scales. However, for diversity of knowledge, we find that local homogeneity performs best in the long-run, because it maintains global diversity, and thus the knowledge-generating ability of the group, for a longer period.
Informal discussion plays a crucial role in democracy, yet much of its value depends on diversity. We describe two models of political discussion. The purposive model holds that people typically ...select discussants who are knowledgeable and politically similar to them. The incidental model suggests that people talk politics for mostly idiosyncratic reasons, as by-products of nonpolitical social processes. To adjudicate between these accounts, we draw on a unique, multisite, panel data set of whole networks, with information about many social relationships, attitudes, and demographics. This evidence permits a stronger foundation for inferences than more common egocentric methods. We find that incidental processes shape discussion networks much more powerfully than purposive ones. Respondents tended to report discussants with whom they share other relationships and characteristics, rather than based on expertise or political similarity, suggesting that stimulating discussion outside of echo chambers may be easier than previously thought.
Data collected from mobile phones have the potential to provide insight into the relational dynamics of individuals. This paper compares observational data from mobile phones with standard ...self-report survey data. We find that the information from these two data sources is overlapping but distinct. For example, self-reports of physical proximity deviate from mobile phone records depending on the recency and salience of the interactions. We also demonstrate that it is possible to accurately infer 95% of friendships based on the observational data alone, where friend dyads demonstrate distinctive temporal and spatial patterns in their physical proximity and calling patterns. These behavioral patterns, in turn, allow the prediction of individual-level outcomes such as job satisfaction.
PDF
