The digital evolution of Occupy Wall Street Emilio Ferrara –SOIC –CNetS–IU Bloomington { [email protected]
Joint work with: MD Conover, C Davis, K McKelvey, F Menczer and A Flammini
The truthy project Meme diffusion on Social Media
Motivations of the protest Key dates and events Social and wealth inequalities, #occupywallstreet Adbusters taxation disparities Sep 17th, 2011 – Zuccotti park Non sustainable capitalistic encampment market models May 1st, 2012 – Attempt to Political corruption, corporate revive the movement influence of government Massive on‐the‐ground protests in NY, DC and [1] Mottos and Motives California “We are the 99%”
movement Pacifist protest
Occupy [1] http://en.wikipedia.org/wiki/Timeline_of_Occupy_Wall_Street on What’s
Online Research Outline Research connectivity Did What’s discourse? What How How information
the
Occupy
much did
type questions:
the
protesters Social
impact of demographics
localized
on change and
users
OSM
interests?
Occupy
use online
is? the
Media? Online
diffusion
of
users’ of involved
Occupy
Social
Occupy
behaviors,
of
users in Occupy
Media
OSM
on
(OSM)? ‐
OSM? related
Geocoding locations Data Collection [1]
Data from Idea: People Only “Temporal” “Geography” GPS contains and news committed
collected Occupy Random Occupy Domestic
during coordinates)
users’ retrieve ~1% on (Progressives Total Any From Total Any From Total Any Total Any From
from
in
dataset
corpus corpus
OSM
geo
sample Twitter
dataset
tweet tweet tweet tweet
politics
encampments of of of of Jun Sep Jul of
to 7.74M 1.82M 825K 1.5M self marches
3
‐
1 total 1 garden
rd
data
[1] produced containing containing containing st geo st spread
, , , [1]
:
2011
corpus 2011
‐ 2011 tweets tweets 2.0)
: reported tweets tweets ‐ hose ‐
tweets
data
(e.g.,
to to to
(10%
(baseline)
[676K Mar [259K Aug
Aug by
produced
were osor #ows (top #tcot or #ows
sample
a
12
31 random 31
RT] RT]
th st st
rate) ,
, ,
2012 2012 2012 #occupy{*} #occupy{*}
produced produced
by conservatives
fuzzy blacklist Result: Methods: Goal: politics of locations accuracy volume
set
447K [3
Occupy
of months
25K distinct
by by
geocoding string
55.7% 257K 68K
w users ows users
before on
+ level
Bing
users
distinct whitelist Twitter)
and distinct
matching
ows]
geocoded and
high
API Domestic
users traffic
or users w/
#p2 29.3%
‐
+ + high
The geography of Occupy
Volume of traffic per state NY, California and DC are the main actors of the Occupy discourse. Some states very active in political discourse, such as Kentucky or Alabama, show little to no interest in Occupy‐related topics. Deviation from the baseline The intensity in the color represents how much the amount of Occupy‐related traffic deviates from that of domestic politics per state.
Ratio of Content Production to Consumption 4
3
2 Content Stream 1 Domestic
Ratio 0 Occupy Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York Carolina North DakotaNorth Ohio Oklahoma Oregon Pennsylvania Island Rhode South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington Virginia West Wisconsin Wyoming
State
Content production and consumption Ratio = # RT originating from users in the state / # RT retweeted by users in the state Proportion of Retweet Traffic by State
0.25 0.20 0.15 0.10 stream 0.05 Domestic 0.00 New York California of Columbia District Florida Texas Illinois Kentucky Massachusetts Wisconsin Oregon New Jersey Alabama Georgia Pennsylvania Michigan Arizona Virginia Washington Colorado CarolinaNorth Minnesota Missouri Maryland Nevada Ohio Oklahoma Carolina South Indiana Tennessee Montana Louisiana New Hampshire Island Rhode Kansas Hawaii Alaska Utah Mississippi Wyoming Iowa Maine New Mexico Connecticut Arkansas Vermont Idaho Delaware Nebraska West Virginia DakotaNorth DakotaSouth Occupy Proportion of Total Traffic Proportion Total of
State (Ordered by Maximum for Each State)
Content diffusion
NY NY
DC DC CA CA
Interstate communication Occupy‐related discourse show a prominent hub‐and‐spoke structure differently from domestic politics (on the left). Multiscale backbone extraction –confidence level 0.15 Collective Resource framing mobilization
Ratio = Language and framing Collective framing: the social processes whereby movement participants negotiate the shared language and narrative frames that help define the movementʹs identity and goals.
Resource mobilization: the work to marshal the physical and technological infrastructure, human resources, and financial capital necessary to sustain ongoing activity.
Local vs. global communication Occupy communication patterns exhibit heightened diagonal activity (more than 3 times) than domestic politics ones.
Occupy discourse on Twitter has highly localized geospatial structure: a large amount of traffic is produced and consumed locally per state. This might be explained by Resource Mobilization. analysis ‐ Interstate communication is driven by high‐profile locations acting as information broadcasters. This geo might represent the Collective Framing process. of
Proximity to on‐the‐ground events plays a big role: users from NY, DC and California are the main actors of the discourse. They produce much more Occupy‐related information than that they consume, unlike other states. Summary
The evolution of Occupy This sign was put in front of a media tent at the Occupy Toronto camp in St. James Park (Toronto). Image by Hillary Burridge. Event
Occupy Wall Street Traffic Volume Initial Protests 30000 Initial Arrests 25000 Foley Square March 20000 Times Square Protests 15000 Union Square March Tweets 10000 Zuccotti Cleared
5000 Counter Protest
0 Egyptian Elections 09/11 10/11 11/11 12/11 01/12 02/12 03/12 04/12 05/12 06/12 07/12 08/12 09/12 May Day Strike Date
Activity volume On‐the‐ground events (circles) and Twitter data‐stream outages (blue bands) are highlighted. Bins have 12‐hours length.
Politics and protest keywords The top hashtags adopted by the 25K random users related to domestic politics and foreign social movements. Attention Allocation Topic Occupy 0.4 Domestic
Revolution 0.3 Engaged User Attention Ratio
0.0 0.2 0.1
0.2 Engaged User Ratio 0.1 0.3
0.4
0.5 0.0 0.6 06/11 07/11 08/11 09/11 10/11 11/11 12/11 01/12 02/12 03/12 04/12 05/12 06/12 07/12 08/12 09/12 Date
Attention allocation Engaged User Ratio describes the proportion of active users in each time‐step who produced at least one topically‐related tweet. Engaged User Attention Ratio describes, among these users, the share of average attention allocated to each topic.
In−Group Connectivity Among Occupy Users
0.40 Group −
0.35 Tweet Type
retweets 0.30 mentions 0.25
0.20 Proportion of Activity In Proportion of Activity 06/11 07/11 08/11 09/11 10/11 11/11 12/11 01/12 02/12 03/12 04/12 05/12 06/12 07/12 08/12 09/12 Date
In‐group connectivity Reported values represent means and 95% confidence intervals for each time‐step. Demography of supporters (I)
Occupy discourse on Twitter is highly correlated in time with on‐the‐ground events. Spikes and high volume of traffic coincide with relevant analysis protests and police actions, marches and strikes.
The phase of explosive growth has exhausted few weeks after the beginning of the protest. temporal
of
The volume of Occupy‐related traffic has diminished by orders of magnitude in the latest observation period. Summary (II) Occupy captured the attention of users with pre‐
existing interests in politics and social protests.
Occupy users’ interests and amount of attention analysis
dedicated to politics and social discourse did not exhibit any remarkable variation over time.
Occupy users were already highly temporal
interconnected before the movement’s start. of
The extent to which Occupy users interacted before the movement’s start and at the end of the observation period is substantially unchanged. Summary
How groups of users create, interact and evolve in Online Social Media? work
Can we generalize some features observed for Occupy (e.g., explosive growth, fast decay, etc.) future
to other classes of topics discussed on OSM? and
How the social and the topical space interact each other to determine the success of certain topics of discussion and the failure of the vast majority of the others? Current Mohsen Jafari-Asbagh Onur Varol Emilio Ferrara Emilio Fil Menczer Thanks! References • • Wall LSONE PLoS Flammini. MD Social Flammini. MD
Conover, Conover,
Street.
Movement Sandro Flammini Sandro Bruno Conçalves Bruno Jacob Ratkiewicz Jacob Lilian Weng
The The (2013)
LSONE PLoS
E C
Digital Geospatial
Ferrara, Davis,
Communication
Evolution
E (in
F
Ferrara, Alex Vespignani Mark Meiss Alex Rudnick Luca Aiello
Menczer, Characteristics preparation)
of
F
Network.
Menczer,
Occupy A
of Mike Conover Johan Bollen Johan Przemek Grabowicz Karissa McKelvey
a
A