Broad Set Of Users Research Articles

Conspiracy vs science: A large-scale analysis of online discussion cascades.

With the emergence and rapid proliferation of social media platforms and social networking sites, recent years have witnessed a surge of misinformation spreading in our daily life. Drawing on a large-scale dataset which covers more than 1.4M posts and 18M comments from an online social media platform, we investigate the propagation of two distinct narratives–(i) conspiracy information, whose claims are generally unsubstantiated and thus referred as misinformation to some extent, and (ii) scientific information, whose origins are generally readily identifiable and verifiable. We find that conspiracy cascades tend to propagate in a multigenerational branching process whereas science cascades are more likely to grow in a breadth-first manner. Specifically, conspiracy information triggers larger cascades, involves more users and generations, persists longer, and is more viral and bursty than science information. Content analysis reveals that conspiracy cascades contain more negative words and emotional words which convey anger, fear, disgust, surprise and trust. We also find that conspiracy cascades are much more concerned with political and controversial topics. After applying machine learning models, we achieve an AUC score of nearly 90% in discriminating conspiracy from science narratives using the constructed features.We further investigate user’s role during the growth of cascades. In contrast with previous assumption that misinformation is primarily driven by a small set of users, we find that conspiracy cascades are more likely to be controlled by a broader set of users than science cascades, imposing new challenges on the management of misinformation. Although political affinity is thought to affect the consumption of misinformation, there is very little evidence that political orientation of the information source plays a role during the propagation of conspiracy information; Instead, we find that conspiracy information from media outlets with left or right orientation triggers smaller cascades and is less viral than information from online social media platforms (e.g., Twitter and Imgur) whose political orientations are unclear. Our study provides complementing evidence to current misinformation research and has practical policy implications to stem the propagation and mitigate the influence of misinformation online.

Designing Analog Games that Engage Girls with Computer Science Concepts

This design case describes the development of three analog games intended to introduce middle-school-age girls to core computer science (CS) concepts. We describe the learning objectives, game mechanics, and narrative elements of each game, and some key problems and decisions that we confronted during the design process. Our design process was guided by two key goals and assumptions: (a) the games should help players develop a situated understanding of CS concepts through engaging them in computational thinking (CT) practices associated with each concept, and (b) game mechanics and story elements should be meaningfully integrated with and supportive of the games’ learning objectives. We discuss several challenges that we encountered in the design process, both in identifying CT practices that lent themselves to game mechanics, and in finding ways to embed mechanics into stories in a meaningful way. Data from gameplay sessions suggests that, on the whole, girls found the games engaging and improved their understanding of CS concepts. However, we conclude that we were only partially successful in achieving our design goals. Testing the facilitator guides with a broader set of users and integrating the facilitator role into gameplay and story are potential goals for future work.

A Cloud-based Framework for Implementing Portable Machine Learning Pipelines for Neural Data Analysis.

Cloud-based computing has created new avenues for innovative research. In recent years, numerous cloud-based, data analysis projects within the biomedical domain have been implemented. As this field is likely to grow, there is a need for a unified platform for the developing and testing of advanced analytic and modeling tools that enables those tools to be easily reused for biomedical data analysis by a broad set of users with diverse technical skills. A cloud-based platform of this nature could greatly assist future research endeavors. In this paper, we take the first step towards building such a platform. We define an approach by which containerized analytic pipelines can be distributed for use on cloud-based or on-premise computing platforms. We demonstrate our approach by implementing a portable biomarker identification pipeline using a logistic regression model with elastic net regularization (LR-ENR) and running it on Google Cloud. We used this pipeline for the diagnosis of Parkinson's disease based on a combination of clinical, demographic, and MRI-based features and for the identification of the most predictive biomarkers.

Detecting Effective Tobacco Control Messages via Linguistic Analysis and Item Response Theory

Abstract Current health communication research on tobacco control often examines the persuasion effects of messages in an experimental setting, which produces small effect sizes and limits the external validity of how well the tested messages will perform in real word settings. In the new media landscape, (anti)smoking and (anti)vaping messages are posted, shared, and disseminated across media platforms by a broader set of users. Tracking the persuasion effects of each message can be challenging with the experimental approaches. Novel analytic methods are needed to evaluate the effective strategies for tobacco control communication. We apply linguistic analysis and item-response theory to antismoking/antivaping messages to detect their persuasion effects on cognitive and emotional outcomes at an individual message level. Methods: We recruited respondents from social media and crowdsourcing platforms (n = 6,566). The eligible current smokers were randomly assigned to one of the 80 antismoking and antivaping messages, or 16 food advertisements (the control group). We measured attitudes toward vaping/smoking, emotional arousal, and intention to quit smoking or vape. We mined text data from each stimulus message to examine their linguistic characteristics and its links to the persuasion outcomes. Results: Majority of participants were White (86%) and female (55%). Antismoking messages were more likely to reveal anxiety (P = 0.01) and dangers or concerns (P < 0.01), compared to the control messages; and express high expertise and confidence compared to antivaping messages (P = 0.04). We report linguistic properties of each message and their relationship to antismoking attitudes, emotional arousal, intention to quit cigarettes, and intention to vape. Visualized patterns of message effectiveness demonstrate text/image-based antivaping messages, compared to video-based antivaping messages, unintentionally increased participants' favorable attitudes toward e-cigarettes. Conclusions: These message-level analyses can help identify best candidate messages that generate positive persuasion outcomes, which, in turn, can inform the selection of messages for health education and campaigns.

Mini-me: Why do climate scientists’ misunderstand users and their needs?

Increasingly climate scientists and the users of climate information are being asked to deliberately co-produce knowledge to improve decision-making about adaptation to climate change. To do this, scientists not only need to be committed and willing to interact with users but also have the capacity to listen, understand, and respond to their needs. Yet little is known about how climate scientists perceive users and respond to their needs when deliberately co-producing knowledge. Using the case study of the UK Climate Projections 2009 (UKCP09) we seek to address this gap. Drawing on interviews with climate scientists, boundary workers, and government officials involved in UKCP09, we investigate how perceptions of users and their needs are constructed as well as the difficulties in responding to them. Our research shows that climate scientists struggle to respond to users other than a small cadre of actors like themselves – highly technical and highly numerate – mini-mes; as what constitutes ‘credible, usable, and relevant’ science is different for users and scientists. Others involved in UKCP09 considered a broader set of users, with more heterogeneous capacities, as the target audience. We find that the climate scientists’ narrow perceptions of users were strongly influenced by (i) their past experiences; (ii) the level and type of scientist-user interactions; and (iii) the institutional setting in which the science took place. This research suggests that climate scientists need broader social support from other experts as well as institutional goals geared towards a broader set of users if they are to successfully co-produce climate knowledge.

“Re-claiming” Land in The Gambia: Gendered Property Rights and Environmental Intervention

By definition, land reclamation programs render marginally productive land resources more valuable to a broader set of users. The question of who gets access to rejuvenated lands is often highly political, however. Environmental managers “reclaim” land resources by rehabilitating them, but they simultaneously reanimate struggles over property rights in the process, allowing specific groups of resource users to literally and figuratively “re-claim” the land. Relying on data gathered during fourteen months of field work between 1989 and 1995, this paper analyzes the openings created by environmental policy reforms introduced over the past two decades along The Gambia River Basin, and the tactics and strategies rural Gambians have developed to manipulate these policies for personal gain. Specifically, I demonstrate how women market gardeners pressed “secondary” usufruct rights to great advantage to ease the economic impact of persistent drought conditions for the better part of a decade, only to have male lineage heads and community leaders “re-claim” the resources in question through donor-generated agroforestry and soil and water management projects. This is thus a study of the responses different community groups have made to a shifting international development agenda centered on environmental goals. It is simultaneously an analysis of those environmental policies and practices and their impact on gendered patterns of resource access and control within a set of critical rural livelihood systems.

Initial graphics exchange specification: Successes and evolution

The Initial Graphics Exchange Specification (IGES) arrived on the CAD/CAM stage in late 1979 and has enjoyed substantial attention from a broad set of users and implementors since. As the term initial reflected, the first release was only a beginning and IGES continues to be an active organization, as well as an evolving CAD/CAM specification. This paper reviews some of the key events and efforts of the IGES community in furthering the quality and scope of this important interface standard.