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{"id":717,"date":"2018-11-06T15:07:45","date_gmt":"2018-11-06T15:07:45","guid":{"rendered":"https:\/\/blog.msomma.catapult.bates.edu\/?p=31"},"modified":"2018-11-06T15:07:45","modified_gmt":"2018-11-06T15:07:45","slug":"response-to-feminist-data-visualization","status":"publish","type":"post","link":"https:\/\/courses.shroutdocs.org\/dcs104-fall2018\/2018\/11\/06\/response-to-feminist-data-visualization\/","title":{"rendered":"Response to Feminist Data Visualization"},"content":{"rendered":"<p>Looking back at last week, I enjoyed reading &#8220;Response: Using metadata to find Paul Revere.&#8221;\u00a0 The author highlighting something i had not considered when conducting network analysis.\u00a0 \u00a0Without any prior knowledge of the topic, bias could arise from the analysis.\u00a0 Meaning, the results from network analysis only are meaningful in the context of prior knowledge. This is a really good point, and something worth considering when conducting the network analysis for the interviews.<\/p>\n<p>For this week&#8217;s reading, I think it brings up many good points.\u00a0 It seems the problem the authors are attempting to create is the reductive nature of data visualizations.\u00a0 There tends to be a lack of context,\u00a0 overall lack of methods, and acknowledgment.\u00a0 Admittedly, I never considered employing feminist theory to correct for this issue, but it seems like a viable option.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Looking back at last week, I enjoyed reading &ldquo;Response: Using metadata to find Paul Revere.&rdquo;&nbsp; The author highlighting something i had not considered when conducting network analysis.&nbsp; &nbsp;Without any prior knowledge of the topic, bias could arise from the analysis.&nbsp; Meaning, the results from network analysis only are meaningful in the context of prior knowledge. &hellip; <\/p>\n<p><a href=\"https:\/\/blog.msomma.catapult.bates.edu\/uncategorized\/response-to-feminist-data-visualization\/\">Continue reading<span> &#8220;Response to Feminist Data Visualization&#8221;<\/span><\/a><\/p>\n","protected":false},"author":197,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"class_list":["post-717","post","type-post","status-publish","format-standard","hentry","category-class"],"_links":{"self":[{"href":"https:\/\/courses.shroutdocs.org\/dcs104-fall2018\/wp-json\/wp\/v2\/posts\/717","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/courses.shroutdocs.org\/dcs104-fall2018\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/courses.shroutdocs.org\/dcs104-fall2018\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/courses.shroutdocs.org\/dcs104-fall2018\/wp-json\/wp\/v2\/users\/197"}],"replies":[{"embeddable":true,"href":"https:\/\/courses.shroutdocs.org\/dcs104-fall2018\/wp-json\/wp\/v2\/comments?post=717"}],"version-history":[{"count":3,"href":"https:\/\/courses.shroutdocs.org\/dcs104-fall2018\/wp-json\/wp\/v2\/posts\/717\/revisions"}],"predecessor-version":[{"id":1521,"href":"https:\/\/courses.shroutdocs.org\/dcs104-fall2018\/wp-json\/wp\/v2\/posts\/717\/revisions\/1521"}],"wp:attachment":[{"href":"https:\/\/courses.shroutdocs.org\/dcs104-fall2018\/wp-json\/wp\/v2\/media?parent=717"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/courses.shroutdocs.org\/dcs104-fall2018\/wp-json\/wp\/v2\/categories?post=717"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/courses.shroutdocs.org\/dcs104-fall2018\/wp-json\/wp\/v2\/tags?post=717"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}