Quantifying Biases in Online Information Exposure

Our consumption of online information is mediated by filtering, ranking, and recommendation algorithms that introduce unintentional biases as they attempt to deliver relevant and engaging content. It has been suggested that our reliance on online technologies such as search engines and social media may limit exposure to diverse points of view and make us vulnerable to manipulation by disinformation. In this paper, we mine a massive dataset of Web traffic to quantify two kinds of bias: (i) homogeneity bias, which is the tendency to consume content from a narrow set of information sources, and (ii) popularity bias, which is the selective exposure to content from top sites. Our analysis reveals different bias levels across several widely used Web platforms. Search exposes users to a diverse set of sources, while social media traffic tends to exhibit high popularity and homogeneity bias. When we focus our analysis on traffic to news sites, we find higher levels of popularity bias, with smaller differences across applications. Overall, our results quantify the extent to which our choices of online systems confine us inside "social bubbles."Comment: 25 pages, 10 figures, to appear in the Journal of the Association for Information Science and Technology (JASIST

The Role of Diverse Strategies in Sustainable Knowledge Production

Online communities are becoming increasingly important as platforms for large-scale human cooperation. These communities allow users seeking and sharing professional skills to solve problems collaboratively. To investigate how users cooperate to complete a large number of knowledge-producing tasks, we analyze StackExchange, one of the largest question and answer systems in the world. We construct attention networks to model the growth of 110 communities in the StackExchange system and quantify individual answering strategies using the linking dynamics of attention networks. We identify two types of users taking different strategies. One strategy (type A) aims at performing maintenance by doing simple tasks, while the other strategy (type B) aims investing time in doing challenging tasks. We find that the number of type A needs to be twice as big as type B users for a sustainable growth of communities.Comment: 10 pages, 3 figure

A Novel Application: Using Mobile Technology to Connect Physical and Virtual Reference Collections

This chapter describes an innovative implementation of the use of iPad kiosks to blur the lines between physical and virtual library collections. Providence College’s Phillips Memorial Library + Commons began lending iPads to students, faculty, and staff in 2012. In addition to lending the devices, library staff dedicated time to learning about both task-based and subject-based mobile applications that would be of use to our community. A small group of library staff tested, discussed, and vetted a variety of apps that would be deployed on the iPads to be lent out. Efforts were made to promote the use and discovery of various apps on the devices through thoughtful organization of the apps on the devices themselves, programming around applications, and the creation of an online research guide designed to teach more about the apps. Despite these initiatives, assessment data from the iPad lending program collected over the course of five semesters suggests that patrons borrowing the iPads are using them primarily for accessing the Internet (Safari, Chrome, etc.), social media (Facebook, Twitter, etc.), and consuming media (YouTube, Netflix, Pandora, Spotify, etc.). With this data in mind, library staff began to think of alternative ways to connect our patrons with useful, content-based, mobile applications. Drawing on research around the Internet of Things and the integration of digital technologies with our physical lives, the Digital Publishing Services Coordinator suggested positioning iPad kiosks strategically within the library’s physical book collection as a means to connect patrons browsing a given area of the stacks with the library’s online resources related to that subject area. The library’s Commons Technology Specialist had experience with iPad kiosks and programming the iPads as he had managed the logistics of the iPad lending program since its inception. Working collaboratively, these colleagues devised a way to image the iPads for public use and load them with subject-specific apps as well as links to library databases and open web resources. The team chose to use Scalar as the primary content management tool for kiosk content. This chapter provides details about the selection and deployment of content for the Theology Kiosk, signage and communications created to attract patrons to the kiosk, and initial data about kiosk use. The piece concludes with a review of the kiosk project and an outline of future planning related to the project (staff time, hardware and software requirements, usability testing, scaling the project, etc.)

Analysis of dependence among size, rate and duration in internet flows

In this paper we examine rigorously the evidence for dependence among data size, transfer rate and duration in Internet flows. We emphasize two statistical approaches for studying dependence, including Pearson's correlation coefficient and the extremal dependence analysis method. We apply these methods to large data sets of packet traces from three networks. Our major results show that Pearson's correlation coefficients between size and duration are much smaller than one might expect. We also find that correlation coefficients between size and rate are generally small and can be strongly affected by applying thresholds to size or duration. Based on Transmission Control Protocol connection startup mechanisms, we argue that thresholds on size should be more useful than thresholds on duration in the analysis of correlations. Using extremal dependence analysis, we draw a similar conclusion, finding remarkable independence for extremal values of size and rate.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS268 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

The Same Antecedents Do Not Fit All Activities: An Activity-specific Model of Personal Internet Use in Workplace

IT devices connected to Internet, such as computers, tablets and smartphones, are commonly used in organizations. At the same time, organizational employees increasingly perform non-work related activities at work by using the IT resources, which is defined as personal Internet use (PIU) in workplace. Multiple models have been developed by previous studies to investigate why employees perform PIU. These studies consider all PIU activities as a uniform behavior. However, literature suggests that there are different types of PIU activities. Therefore, it is with limitations to consider PIU behavior and its antecedents uniformly for all activities, given that PIU behavior may differ significantly when bounded with the different activities. As a first step to close the gap, we examine separately the antecedents of three types of PIU activities: non-work related emailing activities, browsing activities, and online financial activities, to validate our hypothesis that the same antecedent does not explain all PIU activities. Our study contributes to research by demonstrating the necessity to separately examine different types of PIU activities when investigating why employees perform PIU