Large‐scale e‐mail campaigns are a staple in the modern environmental movement. Interest groups increasingly use online mobilizations as a way to raise awareness, money, and membership. There are legitimate political, economic, and organizational reasons for doing so, but these gains may come at the expense of a more substantial and efficacious role for citizens who wish to use e‐mail to engage in public participation. This paper situates a close examination of the 1000 longest modified MoveOn. Org‐generated e‐mails sent to the Environmental Protection Agency (EPA) about its 2004 mercury rulemaking, in the broader context of online grassroots lobbying. The findings indicate that only a tiny portion of these public comments constitute potentially relevant new information for the EPA to consider. The vast majority of Move On comments are either exact duplicates of a two‐sentence form letter, or they are variants of a small number of broad claims about the inadequacy of the proposed rule. This paper argues that norms, rules, and tools will emerge to deal with the burden imposed by these communications. More broadly, it raises doubts about the notion that online public participation is a harbinger of a more deliberative and democratic era.
Large volume public comment campaigns and web portals that encourage the public to customize form letters produce many near-duplicate documents, which increases processing and storage costs, but is rarely a serious problem. A more serious concern is that form letter customizations can include substantive issues that agencies are likely to overlook. The identification of exact-and near-duplicate texts, and recognition of unique text within nearduplicate documents, is an important component of data cleaning and integration processes for eRulemaking. This paper presents DURIAN (DUplicate Removal In lArge collectioN), a refinement of a prior near-duplicate detection algorithm DURIAN uses a traditional bag-of-words document representation, document attributes ("metadata"), and document content structure to identify form letters and their edited copies in public comment collections. Experimental results demonstrate that DURIAN is about as effective as human assessors. The paper concludes by discussing challenges to moving near-duplicate detection into operational rulemaking environments.
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