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• 1 2016-12-15T09:01:35-08:00 The New York Times Project 33 plain 2016-12-18T10:37:05-08:00 To track the evolution of language used when discussing issues related to Women and Girls in the media, I accessed 80 articles published by The New York Times (NYT) between 1940 and 2016. This page presents a data visualization of the entirety of the corpora showing which terms have been used most frequently between these years, and how the frequency has changed over time. In examining the results, I asked questions relating to how language surrounding Women and Girls changed, whether there was any continuity of certain terms throughout history and whether the language shift showed any evidence of progression towards feminine subjectivity.
  
  Below you will find an interactive graphic generated by Voyant which provides a visual analysis of linguistic trends using a corpus composed of 80 articles from The New York Times relating to "Women and Girls" between the years 1940 and 2016. While the data visualization presented provides interesting information, it also evokes further questions pertaining to cultural understandings of women's issues and interests as presented in the media. Some trends are indicative of historical events affecting women. For example, clicking the word "war" in the Cirrus word cloud, we can see a graph appear in Trends that shows a strong decline near the beginning of the corpus, obviously related to women's involvement in World War II until its ending. Other trends evoke binaries historically placed on women's roles in society; a search for children* (where the * stand in as a variable of different endings), college*, and work*, in the Trends search bar, yields a graph presenting college* and work* following a loosely congruent structure, whereas children* presents inverted results compared to the two previous terms over time. Is this reflective of a continuous narrative limiting women to either the public or private sphere? There are many other inferences and questions that can come from comparing and contrasting numerous other terms from the corpus in question.
  
  The following pages contain Voyant analyses for articles split into groupings of twenty years (scores) for the purpose of presenting shifts in media language with relation to the core issues of the various feminist waves. They are accompanied by points of interest that I have personally noted in my research, as well as images and short videoclips which relate to different feminist theorists and movements of the era to provide context to possible influences.
  
  A few notes on using Voyant:
  
  • Reader contains the entire text being analyzed by Voyant if you're interested in scrolling though it fully.
  
  •Contexts shows the first five words surrounding your chosen term as it appears throughout the text if you need context at a glance.
  
  • Don’t be fooled by the Trends graph. Pay attention to how the y-axis labelled “Raw Frequencies” changes by clicking on individual terms in the word cloud to better show results to scale.
  
  • Likewise, the x-axis represents the years 1940-2016, though it does not allow for precise labelling. The word counts of various sections are not completely equal, so exercise caution when attempting to date results. 
  
  More information on how and why I used Voyant can be found here,
   

  I urge you to interact with the embedded graphics, exploring the project in which ever format suits you best!

  
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  This project acts as an example of what can be accomplished by text mining media data using a select number of tools. Any inferences or conclusions regarding linguistic trends are purely provisional as they have been made using a fractional percentage of all articles related to "Women and Girls" that have been published by the NYT within the set time-frame and may therefore be largely inaccurate.
  
  All of the data presented has come from either The New York Times website,or ProQuest Historical Newspapers accessed through the University of Guelph. (See bibliography for further information)
   
  This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.