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Saturday, September 27 • 11:01 - 11:20
"Examining Political Mobilization of Online Communities Through E-Petitioning Behavior in We The People"

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Background: We discuss We the People (WtP), an unprecedented US national experiment in using social media to enable users to propose and solicit support for policy suggestions. Using WtP, users generate petitions for actions of the petitioner’s choosing and employ other social media to solicit signatures for their proposals; with sufficient signatures, petitioners may obtain a response from the Administration (see https://petitions.whitehouse.gov/ ). 

In the wake of the Sandy Hook shootings on December 14, 2012, President Obama responded to 33 petitions initiating policy proposals. He pledged a national conversation about gun control, fueled by the single largest petition to appear on WtP, which advocated that the country “Immediately address the issue of gun control through the introduction of legislation in Congress” and which gathered over 195,000 signatures in less than a week. We apply Baumgartner and Jones's (1993; True, Jones & Baumgartner, 2006) work on agenda setting and punctuated equilibrium, which suggests that policy issues may lie dormant until some event triggers attention from the the public. E-petitioning may play a role in this process by enabling a process of definition and mobilization that can move issues to the forefront of policy attention, unless countered by “negative feedback.” We focus on 21 petitions initiated during this week in opposition to gun control, which we view as mobilized efforts to maintain stability and equilibrium in a policy system threatening to change. 

Objective: While e-petitioning is common, few studies address this data (but see Hale, Margetts, & Yasseri, 2013 on Britain; Jungherr & Jurgen, 2010 on Germany). This paper aims to reveal patterns of petition co-signing that are indicative of mobilized opposition to gun control. 

Methods: Using market basket analysis and other data mining techniques on petition and coded signature data publicly available on the WtP website (see https://petitions.whitehouse.gov/developers), we analyzed 21 oppositional petitions, which attracted over 120,000 distinct signatures. It was evident that individual signers had signed more than one petition. Table 1 in the Appendix presents title and signature counts for each petition; market basket analysis is described in the Appendix. 

Results: We sorted the 21 petitions into thematic clusters, finding three: invest in mental health care; guard our schools; and support law-abiding gun owners. The directed graphs that result from Step 4 of our methodology are shown in the appendix. The structure of these graphs gave rise to a few early conclusions: 
At the largest confidence value (50%), the seven petitions in the cluster “Support law-abiding gun owners” were highly connected on the basis of common signers and constituted a “frequent itemset”; petitions in the other two categories are not highly connected. That is, individuals signing a petition in this itemset were more likely to sign others in the set, but not petitions in the other two clusters. With confidence lowered to 40%, additional associations begin to appear between the first itemset and others. Additional conclusions will be presented in an expanded version of this document. 

Conclusions and Future Work: Community detection techniques and social network analysis will be used to to determine if groups of individuals sign similar anti-gun control petitions, thus suggesting the creation of “communities” whose actions are similarly aligned in opposition to gun control.

Speakers
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Feng Chen

College of Computing & Information, University at Albany, State University of New York
avatar for Catherine Leigh Dumas

Catherine Leigh Dumas

The College of Computing & Information, State University of New York at Albany
PhD student Informatics SUNY Albany | Graduate Studies - Information Science | Instructor SUNY Albany
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Norman Gervais

College of Computing & Information, University at Albany, State University of New York
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Loni Hagen

College of Computing & Information, University at Albany, State University of New York
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Teresa Harrison

College of Computing & Information, University at Albany, State University of New York
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Chris Kotfila

College of Computing & Information, University at Albany, State University of New York
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Dan Lamanna

College of Computing & Information, University at Albany, State University of New York
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S.S. Ravi

College of Computing & Information, University at Albany, State University of New York
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Ozlem Uzuner

College of Computing & Information, University at Albany, State University of New York


Saturday September 27, 2014 11:01 - 11:20
TRS 1-003 Ted Rogers School of Management

Attendees (6)