{"id":412,"date":"2017-10-08T16:48:58","date_gmt":"2017-10-08T23:48:58","guid":{"rendered":"http:\/\/miriamposner.com\/classes\/dh101f17\/?p=412"},"modified":"2017-10-08T16:48:58","modified_gmt":"2017-10-08T23:48:58","slug":"week-1-blog-post-reverse-engineering-robots-reading-vogue","status":"publish","type":"post","link":"http:\/\/miriamposner.com\/classes\/dh101f17\/2017\/10\/08\/week-1-blog-post-reverse-engineering-robots-reading-vogue\/","title":{"rendered":"Week 1 Blog Post (Reverse Engineering “Robots Reading Vogue”)"},"content":{"rendered":"

“Robots Reading Vogue” was a DH project that analyzed visual and semantic trends (amongst others) across over 100 years\u00a0Vogue<\/em>\u00a0magazine data. The trends ranged from hair color of cover models to issue themes based on word co-occurrences. Seeing as\u00a0Vogue<\/em> has been around for over a century, it’s consistent and enduring nature provides a unique and fascinating platform for analyzing popular trends, especially in terms of female fashion.<\/p>\n

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Sources<\/strong><\/p>\n

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As can be assumed by the project title, “Robots Reading Vogue” uses\u00a0Vogue<\/em> magazines as its sources. According to the project’s about page, the total source collection is comprised of over 2,700 covers, 400,000 pages, and six terabytes of data. As with most magazines, the source material is made up of solely words and images.<\/p>\n

Processed<\/strong><\/p>\n

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For visual trends like covers, any image that was not already in an online database had to be manually scanned. In order to standardize covers across decades (accounting for design changes), images had to be hand-aligned.<\/p>\n

The methods used to extract words from specific issues were not specifically identified within the project’s description. However, I would assume that if not already in some sort of pre-existing\u00a0Vogue\u00a0<\/em>database, each individual issue would have had to have been manually scanned into a database. Then the digital representations would have had to been fed through an OCR program like Adobe in order to convert the scanned words into their digital equivalents.<\/p>\n

Presented<\/strong><\/p>\n

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Since there were several different experiments and studies underneath the umbrella of “Robots Reading Vogue”, I will cover only a couple of the main visualizations.<\/p>\n

Cover data was displayed in both a histogram style as well as an overlapping fashion. The histogram displayed color distributions (in terms of RGB) as a histogram year by year. The overlap design took similar covers (same face placements, etc) and overlapped the images to create a sort of generic Vogue\u00a0<\/em>cover.<\/p>\n

Semantic data was modeled both as word clouds as well as line graphs. The word clouds were comprised of words or phrases within a specific category (i.e. “museum” and “painting” in the Art category) with larger words having more mentions. The line graphs charted specific word usage over time. The dynamic graph allowed the inclusion of multiple words, so one could see how the trend of one word compared to others.<\/p>\n","protected":false},"excerpt":{"rendered":"

“Robots Reading Vogue” was a DH project that analyzed visual and semantic trends (amongst others) across over 100 years\u00a0Vogue\u00a0magazine data.<\/p>\n","protected":false},"author":119,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_eb_attr":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-412","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"http:\/\/miriamposner.com\/classes\/dh101f17\/wp-json\/wp\/v2\/posts\/412","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/miriamposner.com\/classes\/dh101f17\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/miriamposner.com\/classes\/dh101f17\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/miriamposner.com\/classes\/dh101f17\/wp-json\/wp\/v2\/users\/119"}],"replies":[{"embeddable":true,"href":"http:\/\/miriamposner.com\/classes\/dh101f17\/wp-json\/wp\/v2\/comments?post=412"}],"version-history":[{"count":0,"href":"http:\/\/miriamposner.com\/classes\/dh101f17\/wp-json\/wp\/v2\/posts\/412\/revisions"}],"wp:attachment":[{"href":"http:\/\/miriamposner.com\/classes\/dh101f17\/wp-json\/wp\/v2\/media?parent=412"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/miriamposner.com\/classes\/dh101f17\/wp-json\/wp\/v2\/categories?post=412"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/miriamposner.com\/classes\/dh101f17\/wp-json\/wp\/v2\/tags?post=412"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}