The Digital Life of Walkable Streets

Walkability has many health, environmental, and economic benefits. That is why web and mobile services have been offering ways of computing walkability scores of individual street segments. Those scores are generally computed from survey data and manual counting (of even trees). However, that is costly, owing to the high time, effort, and financial costs. To partly automate the computation of those scores, we explore the possibility of using the social media data of Flickr and Foursquare to automatically identify safe and walkable streets. We find that unsafe streets tend to be photographed during the day, while walkable streets are tagged with walkability-related keywords. These results open up practical opportunities (for, e.g., room booking services, urban route recommenders, and real-estate sites) and have theoretical implications for researchers who might resort to the use social media data to tackle previously unanswered questions in the area of walkability.Comment: 10 pages, 7 figures, Proceedings of International World Wide Web Conference (WWW 2015

Charm and beauty at the Tevatron

The large heavy quark production cross section in p{bar p} collisions makes the Tevatron an excellent place to study charm and bottom physics. This allows for a rich program of spectroscopy, CP parameter measurements, and searches for new physics

A data driven approach to mapping urban neighbourhoods

Neighbourhoods have been described by the UK Secretary of State for Communities and Local Government as the “building blocks of public service society”. Despite this, difficulties in data collection combined with the concept’s subjective nature have left most countries lacking official neighbourhood definitions. This issue has implications not only for policy, but for the field of computational social science as a whole (with many studies being forced to use administrative units as proxies despite the fact that these bear little connection to resident perceptions of social boundaries). In this paper we illustrate that the mass linguistic datasets now available on the internet need only be combined with relatively simple linguistic computational models to produce definitions that are not only probabilistic and dynamic, but do not require a priori knowledge of neighbourhood names

Participatory Militias: An Analysis of an Armed Movement's Online Audience

Armed groups of civilians known as "self-defense forces" have ousted the powerful Knights Templar drug cartel from several towns in Michoacan. This militia uprising has unfolded on social media, particularly in the "VXM" ("Valor por Michoacan," Spanish for "Courage for Michoacan") Facebook page, gathering more than 170,000 fans. Previous work on the Drug War has documented the use of social media for real-time reports of violent clashes. However, VXM goes one step further by taking on a pro-militia propagandist role, engaging in two-way communication with its audience. This paper presents a descriptive analysis of VXM and its audience. We examined nine months of posts, from VXM's inception until May 2014, totaling 6,000 posts by VXM administrators and more than 108,000 comments from its audience. We describe the main conversation themes, post frequency and relationships with offline events and public figures. We also characterize the behavior of VXM's most active audience members. Our work illustrates VXM's online mobilization strategies, and how its audience takes part in defining the narrative of this armed conflict. We conclude by discussing possible applications of our findings for the design of future communication technologies.Comment: Participatory Militias: An Analysis of an Armed Movement's Online Audience. Saiph Savage, Andres Monroy-Hernandez. CSCW: ACM Conference on Computer-Supported Cooperative Work 201

Growing Asparagus in Minnesota

This archival publication may not reflect current scientific knowledge or recommendations. Current information available from the University of Minnesota Extension: https://www.extension.umn.edu

The ATLAS EventIndex: Full chain deployment and first operation

AbstractThe Event Index project consists in the development and deployment of a complete catalogue of events for experiments with large amounts of data, such as the ATLAS experiment at the LHC accelerator at CERN. Data to be stored in the EventIndex are produced by all production jobs that run at CERN or the GRID; for every permanent output file, a snippet of information, containing the file unique identifier and the relevant attributes for each event, is sent to the central catalogue. The estimated insertion rate during the LHC Run 2 is about 80 Hz of file records containing ∼15 kHz of event records. This contribution describes the system design, the initial performance tests of the full data collection and cataloguing chain, and the project evolution towards the full deployment and operation by the end of 2014

Growing Broccoli and Cauliflower in Minnesota

This archival publication may not reflect current scientific knowledge or recommendations. Current information available from the University of Minnesota Extension: https://www.extension.umn.edu