SoMe Lab Social Media Lab @ UW @somelabresearch @joeeckert #aag2013 Occupied Geographies Relational...

SoMe LabSocial Media Lab @ UW @somelabresearch@joeeckert #aag2013

Occupied GeographiesRelational and Otherwise

Josef Eckert, Department of Geography

Jeff Hemsley, Information SchoolUniversity of Washington

April 11, 2013


Occupy Wall Street

• Included both digitaland urban spaces

• Localized, networkedprocesses

• New social mediatactics


What role does place play within network structures of Twitter?

Are actors both in place and on Twitter interactingwith one another?


Motivation

Twitter and Social Network Analysis seem to be trending right now

#overlyhonestmethods


Motivation

• Urban processes are lived experiences (Lefebvre)

• These experiences are digitally mediated (Crampton, Leszczynski)

• The digital is inextricably part of urban life (Kitchen, Dodge, Zook, Graham)


Motivation

• Twitter as a tactic for organization and protest (Gerbaudo)

• Decentralized, networked organizations of protest (Castells)

• A geographic focus on networks and the role they play in contentious politics (Leitner et. al, Nicholls)

• Moving beyond the geotag as a unit of place (Crampton et. al)


A first cut at exploration….

Testing a “common sense” assumption:

Are protesters that represent themselves as livingin places with protest locations more likely to interact (@-mention) with others that also represent themselvesas living in that place?


Data Gathering

• 10/19/2011 – current day

• Gathered using streaming(now REST) API

• 300k – 1m tweets per day,215 “keyterms”

• Have to slice the data


That’s SoMe Toolkit!


Data Preparation

Six hashtags representative of protest locations: #occupyslc,#occupyportland, #occupyseattle, #occupyhouston, #occupydenver, and #occupyorlando (and #ows for fun)

Reduced dataset to only those users with both in- andout-going @-mention links (those interacting bi-directionally)

Temporally bounded: 7-day (10/19/2011 – 10/25/2011)30-day (10/19/2011 – 11/19/2011)

#ows: 1-day (10/19/2011) – my computer is melting!


Data Preparation: Users “in Place”

Avoiding geotagging, attempting to use user-defined location

Obtained a list of user-defined places for users participatingin a hashtag – checking for alternative city matches (“SLC”)

Used Regular Expression matching to determine if a user was“in place” for a given hashtag (e.g. “Salt Lake | Salt Lake City | SLC”)

SoMe LabSocial Media Lab @ UW

Orlando, 30 days


Denver, 30 days


OWS, *1* day


• QAP Testing Matrices

• QAP uses random Monte Carlo iterations rather than inference metrics

Tests against three null hypotheses:

x1: Users with mutual ties do not @-mentionone another in a way that significantly differsfrom a random distribution

x2: Users in a mutual place do not …

x3: Users with more followers are not @-mentioned…

Step 1: QAP Testing(Quadradic Assignment Problem)

Jeff Joe

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Shawn

Shawn

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0 0

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EYij = β0 + β1X1ij + β2X2ij + β3X3ij

IV: Matrix, # of @-mentions

Intercept

DV: Mutual TieMatrix

DV: Users “inPlace” Matrix

DV: FollowerCount Matrix

Step 2: Fit QAP coefficents to OLS Regression


X1 (mutual tie) X2 ("In Place") X3 (Receiver's Followers) Adjusted R2

Orlando 7-day 0.000 0.018 0.110 0.2608Orlando 30-day 0.000 0.000 0.618 0.2807Houston 7-day 0.000 0.018 0.258 0.4028Houston 30-day 0.000 0.000 0.000 0.395Salt Lake City 7-day 0.000 0.064 0.862 0.3775Salt Lake City 30-day 0.000 0.002 0.018 0.1998Seattle 7-day XXXX XXXX XXXX XXXXSeattle 30-day 0.000 0.001 0.006 0.1629Denver 7-day 0.000 0.424 0.024 0.2665Denver 30-day 0.000 0.000 0.004 0.1516Portland 7-day 0.000 0.766 0.416 0.4472Portland 30-day 0.000 0.000 0.008 0.1267OWS 1-day 0.000 0.000 0.000 0.1572

Insignificance is more interesting….


There’s still much to do

• The model fit could be better

• Analysis across multiple temporal slices

• Application to the other 154 locationalhashtags

• Continued sensitivity testing to confirm that “place matters” in social media network construction. But how?


future directions in visualization

portland network, portland super-clique vignette

Future Directions

Portland, 7 days

Cliques &Topic Modeling


This research was made possible by:NSF Award #1243170INSPIRE: Tools, Models, and Innovation Platforms for Research on Social Media

Thank you! Questions and Suggestions?

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