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Americans Bear Arms – Lia Petronio

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A visualization that is part of graduate Student Lia Petronio’s MFA thesis, entitled “Trigger Events: Mass Shootings, Causality, & Discursive Inertia.” The project explores Mass Shootings from two main viewpoints – Part 1 the ‘events’ and Part 2 the ‘discussion’.

Part 1 maps Mass Shootings and their attributes from 1970 to 2015.  Two views of the data are shown.  “Patterns and Relationships” focuses on tendencies and relationships between a selection of significant variables, with filtering to enable pattern finding and intent driven searches by viewers.  “Location and Frequency” illustrates the geo-locational and temporal attributes highlighting the victim count as well as frequency over time.  Axis filtering on the timeline allows for viewers to find changes in frequency and place types over selected time periods.  Both visualization structures allow for selection of individual Mass Shootings, providing a description of the event and the suspected motive of the shooter.

Part 2 of my thesis will explore the way people use online media in response to Mass Shootings, framing the situation from a collection of perspectives through Twitter communities.  In aggregating the content into a cohesive collection of micro-level studies within the context of a macro-level community, defined by hashtag networks focused around the tag #MassShootings, we can better understand components of the situation. The visualization will identify clusters of dominant opinions, genealogies, and frequencies of hashtags over time.  At a micro-scale it will examine response time and extent, link exchanges, tweet content, and geo-location in response to specific Mass Shootings.

Each study approaches the subject as a collection of units composing the whole, on the premise that individual units are more descriptive in the context of other related units, and that better understanding can be created through design techniques that help us isolate and compare behavior of small units relative to its encompassing structure.

By

Lia Petronio

Graduate Student

 

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