NACIS 2016 Presentation Rex Cammack, University of Nebraska at Omaha Paul Hunt - University of Nebraska at Omaha In this research we are investigating how to turn data flowing through social media hoses into live maps. This research focuses on the graphic representation of location enabled social media data. The first aspect of this project is gathering and storing this zombie data. Decisions about infrastructure and implementation will be outlined regarding issues such as endless verses revolving data storage, spatial or non-spatial data storage, distributive verses aggregated data, raw verses contextual data, and server versus client processing. The results of these infrastructure decisions coupled with map and interactive design choices provide map users with the ability work with data that is more lifelike than raw zombie data. The underlining data flow and processing research will be demonstrated through a case study that looks at temporal and cumulative patterns of tweets about NCAA College football teams.

1. Hashtag to Map:
Transforming Zombie
data to Maps
Rex G Cammack and Paul Hunt
University of Nebraska Omaha
University of Nebraska Lincoln

2. Work Flow
 Problem
 Dream
 Past Development
 Current Flow
 Take a Look
 Future

3. Problem
 Understanding how Fans are Spatial
Distributed
 Does Geographic Theory Apply
 Can We use Social Media to Examine the
Spatial Context in Depth

4. Dream
Theory
 Create an information flow from
Social Media to User that goes
below the surface of community
expression
Practice
 View of the now and then
 Accessible
 Open Data
 Enhancement
 Interpreted

5. Past Development
Year 1
 Geo Fences for data gathering
 What are my Hashtags
 Student Research
 Geo Gathering
 Internal Server Applications
Year 2
 Defined Searches by ####
 Cloud Application
 Partial Data Collection

6. eeK!

7. Current Flow
Twitter
 Built a Twitter Application
 Query the Twitter Hose
 Geo Event – isolating Team
Hushtags
Amazon Cloud
 Hosted Work Flow
 GeoEvent - ArcGIS Server
 IIS - Python to CGI
 Geo Event to Mongo
 Mongo – a nonSQL database
 Hosting Mongo Database service
 Get Request Server Side Script -
Python CGI to Query Mongo
 Server Side Script – Format to JSON
 Passes – JSON back to Client

8. Current Work Flow
Client Application
 We make many App Widgets
 Demo in a moment
Enliven Data
 Raw Twitter data to Mongo
 Started on August 31 2016
 10.5 million Raw
 415,000 Geo location
 200,000 Post Processed
 Script to Enliven the Data and
add to new Mongo Database

9. Take a Look
OSU 1 Week OSU 4 Weeks

10. WATCH OUT!!!

11. Future
Mapping
 Better Client Mapping
 Complex Visualizations
 Point Clusters
 Team – Rivals – Conference
 Others
Data
 Teams
 Natural Language Processing
 Juke tweets
 Ad tweets
 Theme Tweets
 Team Sentiment
 Think Fan Chernov Face
 Location Enhancements
 Distance to Team
 Distance to Home
 Away Tweets

12. Thank You----- Questions
http://icc2017.org/ ICA Maps and the Internet Commission 2017