{"id":14797,"date":"2015-01-27T13:30:18","date_gmt":"2015-01-27T18:30:18","guid":{"rendered":"http:\/\/peterlevine.ws\/?p=14797"},"modified":"2015-01-27T13:30:18","modified_gmt":"2015-01-27T18:30:18","slug":"diagramming-sarah-palins-iowa-speech","status":"publish","type":"post","link":"https:\/\/peterlevine.ws\/?p=14797","title":{"rendered":"diagramming Sarah Palin’s Iowa speech"},"content":{"rendered":"

Northeastern political scientist Nick Beauchamp<\/a> has developed a remarkable, free tool <\/a>(Plot Mapper) that identifies keywords in a stream of text and plots them on a two-dimensional plane. The words are placed automatically but meaningfully (using a form of principal components analysis<\/a>), and a line traces the order in which the ideas unfolded over time.<\/p>\n

Beauchamp’s analysis of the 2015 State of the Union was covered in the Washington Post<\/a>. He demonstrated the neat arc of the president’s rhetoric:<\/p>\n

\"\"<\/a><\/p>\n

I wanted to try the tool, so I looked around for another recent speech that might contrast with the SOTU. Sarah Palin’s Iowa speech has been widely panned on the right<\/a> as well as the left, being called a “tragedy”–or at least “an interminable ramble.” I pasted the text<\/a> into Plot Mapper and this is what I got:<\/p>\n

\"Screen<\/p>\n

I actually think the quality gap between these two texts is a little obscured by this form of analysis. “America,” “country,” and “people” seem to play similar roles in both speeches. We also see an actual organizing structure to Palin’s words: she moves from nationalism through right-populism (real people are conservative) to conclude with the local (veterans in Iowa). Finding such an arc may be giving the speaker a bit too much credit. Nevertheless, the tool has enormous potential for comparing discourse. I’d be especially interested in using it to analyze how people affect each others’<\/em> ideas when they deliberate.<\/p>\n","protected":false},"excerpt":{"rendered":"

Northeastern political scientist Nick Beauchamp has developed a remarkable, free tool (Plot Mapper) that identifies keywords in a stream of text and plots them on a two-dimensional plane. The words are placed automatically but meaningfully (using a form of principal components analysis), and a line traces the order in which the ideas unfolded over time. […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[6],"tags":[],"class_list":["post-14797","post","type-post","status-publish","format-standard","hentry","category-deliberation"],"acf":[],"_links":{"self":[{"href":"https:\/\/peterlevine.ws\/index.php?rest_route=\/wp\/v2\/posts\/14797","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/peterlevine.ws\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/peterlevine.ws\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/peterlevine.ws\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/peterlevine.ws\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=14797"}],"version-history":[{"count":7,"href":"https:\/\/peterlevine.ws\/index.php?rest_route=\/wp\/v2\/posts\/14797\/revisions"}],"predecessor-version":[{"id":14809,"href":"https:\/\/peterlevine.ws\/index.php?rest_route=\/wp\/v2\/posts\/14797\/revisions\/14809"}],"wp:attachment":[{"href":"https:\/\/peterlevine.ws\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=14797"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/peterlevine.ws\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=14797"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/peterlevine.ws\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=14797"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}