Accessing Social Statistics

published or submitted for publicatio

An Internet Heartbeat

Obtaining sound inferences over remote networks via active or passive measurements is difficult. Active measurement campaigns face challenges of load, coverage, and visibility. Passive measurements require a privileged vantage point. Even networks under our own control too often remain poorly understood and hard to diagnose. As a step toward the democratization of Internet measurement, we consider the inferential power possible were the network to include a constant and predictable stream of dedicated lightweight measurement traffic. We posit an Internet "heartbeat," which nodes periodically send to random destinations, and show how aggregating heartbeats facilitates introspection into parts of the network that are today generally obtuse. We explore the design space of an Internet heartbeat, potential use cases, incentives, and paths to deployment

Atlas.txt : Linking Geo-referenced Data to Text for NLG

Peer reviewedPreprin

Mining the Demographics of Political Sentiment from Twitter Using Learning from Label Proportions

Opinion mining and demographic attribute inference have many applications in social science. In this paper, we propose models to infer daily joint probabilities of multiple latent attributes from Twitter data, such as political sentiment and demographic attributes. Since it is costly and time-consuming to annotate data for traditional supervised classification, we instead propose scalable Learning from Label Proportions (LLP) models for demographic and opinion inference using U.S. Census, national and state political polls, and Cook partisan voting index as population level data. In LLP classification settings, the training data is divided into a set of unlabeled bags, where only the label distribution in of each bag is known, removing the requirement of instance-level annotations. Our proposed LLP model, Weighted Label Regularization (WLR), provides a scalable generalization of prior work on label regularization to support weights for samples inside bags, which is applicable in this setting where bags are arranged hierarchically (e.g., county-level bags are nested inside of state-level bags). We apply our model to Twitter data collected in the year leading up to the 2016 U.S. presidential election, producing estimates of the relationships among political sentiment and demographics over time and place. We find that our approach closely tracks traditional polling data stratified by demographic category, resulting in error reductions of 28-44% over baseline approaches. We also provide descriptive evaluations showing how the model may be used to estimate interactions among many variables and to identify linguistic temporal variation, capabilities which are typically not feasible using traditional polling methods

Toward Universal Broadband in Rural Alaska

The TERRA-Southwest project is extending broadband service to 65 communities in the Bristol Bay, Bethel and Yukon-Kuskokwim regions. A stimulus project funded by a combination of grants and loans from the Rural Utilities Service (RUS), TERRA-Southwest has installed a middle-mile network using optical fiber and terrestrial microwave. Last-mile service will be through fixed wireless or interconnection with local telephone networks. The State of Alaska, through its designee Connect Alaska, also received federal stimulus funding from the National Telecommunications and Information Administration (NTIA) for tasks that include support for an Alaska Broadband Task Force “to both formalize a strategic broadband plan for the state of Alaska and coordinate broadband activities across relevant agencies and organizations.” Thus, a study of the impact of the TERRA project in southwest Alaska is both relevant and timely. This first phase provides baseline data on current access to and use of ICTs and Internet connectivity in rural Alaska, and some insights about perceived benefits and potential barriers to adoption of broadband. It is also intended to provide guidance to the State Broadband Task Force in determining how the extension of broadband throughout the state could contribute to education, social services, and economic activities that would enhance Alaska’s future. Results of the research could also be used proactively to develop strategies to encourage broadband adoption, and to identify applications and support needed by users with limited ICT skills.Connect Alaska. The National Telecommunications and Information Administration. General Communications Incorporated.Part 1: An Analysis of Internet Use in Southwest Alaska / Introduction / Previous Studies / Current Connectivity / Analytical Framework and Research Methodology / Demographics / Mobile Phones: Access and Use / Access to the Internet / Internet Useage / Considerations about Internet Service / Interest in Broadband / Sources of News / Comparison with National Data / Internet Use by Businesses and Organizations / What Difference may Broadband make in the Region? / Conclusiongs / Part 2 Literature Review / Reference

Digital Use and Internet Access in Fayetteville, Arkansas

A report on data gathered from a spring 2019 survey by the UA Center for Communication Research. The data will provide the City of Fayetteville with a baseline picture regarding residents’ current levels of internet access, their daily activities online, the importance of the internet to them, and the barriers they see to enhanced online access. Future study will consider the homework gap in homes with K-12 students as well as general internet access issues for residential multi-tenant environments. Data from this survey will inform the City of Fayetteville\u27s Digital Equity Plan

Toward an Interactive Directory for Norfolk, Nebraska: 1899-1900

We describe steps toward an interactive directory for the town of Norfolk, Nebraska for the years 1899 and 1900. This directory would extend the traditional city directory by including a wider range of entities being described, much richer information about the entities mentioned and linkages to mentions of the entities in material such as digitized historical newspapers. Such a directory would be useful to readers who browse the historical newspapers by providing structured summaries of the entities mentioned. We describe the occurrence of entities in two years of the Norfolk Weekly News, focusing on several individuals to better understand the types of information which can be gleaned from historical newspapers and other historical materials. We also describe a prototype program which coordinates information about entities from the traditional city directories, the federal census, and from newspapers. We discuss the structured coding for these entities, noting that richer coding would increasingly include descriptions of events and scenarios. We propose that rich content about individuals and communities could eventually be modeled with agents and woven into historical narratives

Exploring Uncertainty in Geodemographics with Interactive Graphics

Geodemographic classifiers characterise populations by categorising geographical areas according to the demographic and lifestyle characteristics of those who live within them. The dimension-reducing quality of such classifiers provides a simple and effective means of characterising population through a manageable set of categories, but inevitably hides heterogeneity, which varies within and between the demographic categories and geographical areas, sometimes systematically. This may have implications for their use, which is widespread in government and commerce for planning, marketing and related activities. We use novel interactive graphics to delve into OAC – a free and open geodemographic classifier that classifies the UK population in over 200,000 small geographical areas into 7 super-groups, 21 groups and 52 sub-groups. Our graphics provide access to the original 41 demographic variables used in the classification and the uncertainty associated with the classification of each geographical area on-demand. It also supports comparison geographically and by category. This serves the dual purpose of helping understand the classifier itself leading to its more informed use and providing a more comprehensive view of population in a comprehensible manner. We assess the impact of these interactive graphics on experienced OAC users who explored the details of the classification, its uncertainty and the nature of between – and within – class variation and then reflect on their experiences. Visualization of the complexities and subtleties of the classification proved to be a thought-provoking exercise both confirming and challenging users’ understanding of population, the OAC classifier and the way it is used in their organisations. Users identified three contexts for which the techniques were deemed useful in the context of local government, confirming the validity of the proposed methods