Underlying all of the readings is a presumption that unrestrained communication — i.e., “Free Speech” — empowers. To that end, we have several examinations of how to become effective using electronic and social tools or “tactics”: 1) Mobilise, 2) Witness/record, 3) Visualise, 4) Personalize, 5) Humour, 6) contact management, 7) data usage, 8) collective intelligence, 9) Q&A, 10) Investigate/impose. “Blogs & Bullets” examines new media effectiveness; and, “Protest in an Information Society” introduces a limited historical review and Information Communication Technologies (ICT) components/effects.
One compelling thread is the impact of communication on group affiliation and cohesion. It is the underlying ability of the communicated message to form group affiliation and thereby empower protest. In fact, there is a considerable body of research that examines how such affiliations are formed and expose or document these relationships. Psychological precursors as early as 1948 (Tolman), examined the structural components of group relatonships. As early as 1968, MIT’s Jay Forrester described system dynamics mathematically. Then, an effort to document systematic behaviors gave way to a belief in random causality. Just ten years earlier, early mathematical systems had been developed to describe a more reliable, systematic approach (Abelson/Rosenberg, 1958). The seminal work was published in 1976 (Axelrod): Structure of Decision. By the late 1990s, causal mapping had become an academic discipline within the infrmation sciences (IS).
Throughout this developmental period, a variety of diverse applications developed outside academic environments: investment, manufacturing, industrial analysis, educational evaluation. Recently, researchers in Spain have been able to use causal maps to describe protest movements there to demonstrate activism effectiveness.
Early phase development was primarily manual or through administered data instruments. The availability of data from social media has opened a new chapter in the development of causal maps. Normally, causal maps were developed by coding historical information (Mohammed 2000). Harvard’s Institute for Quantative Social Sciences has been one of the centers that has tested statistical applications for causal mapping in the domain of international conflict, voting, and issue management — i.e., Mexican health care. The local firm, Crimson Hexagon has been formed as a commercial vendor for manufacturing systems applications similar to those advocated by MIT’s Jay Forrester, based on linguistic input.
Given the availability fo ICT feeds from Twitter, Facebook, news wire services, etc. it is now possible to automate the development of causal maps to evaluate the effectiveness of the techniques advocated by the authors presented in our class. Using dynamic data it is now possible to develop an assment of group effectiveness in real time. For example, the ICT elements identified by R. Kelly Garrett — i.e., cell phone SMS, eMail, blogs, etc. — can be captured in real time for analysis. Thus, in addition to the tools presented in our readings, we can now evaluate their effectiveness on an insturmentation and message basis in any language.
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