The project I have been working on this semester is an analysis of a list of top 10 feminist speeches from Marie Claire‘s: the 10 Greatest Speeches of all Time by 10 Inspirational Women. The list is not a very homogenous list with a speech dating back to 1588 and the most recent one in 2012. I wanted to know if there was a pattern that I could find in the speeches, something that would connect them to demonstrate why these speeches ended up becoming the top speeches when there are so many contenders to choose from. I also wanted to see if there was a change in the way the women spoke as they did gain more rights and equality in society.
My project began very differently, I first decided on civil rights as a whole, toying with ideas of race and feminism the most before finally deciding on feminism. I had been going to come up with my own compilation of speeches throughout history to analyze before deciding to narrow it down to the the one list I have now. Eight of the ten speeches were easily available, the two that gave me the most trouble were the longest and shortest pieces: A book and a 30 second clip. The clip took so much time because when I searched for it I thought the clip was a part of a longer speech before realizing that it was not, and after more searching I gave looking for it and wrote it down myself. The entire text was only about four sentences. The book was also a little more difficult to find then the speeches but I eventually was able to find a complete pdf that I could then convert to a .txt file.
Before using tools to analyze my documents I wanted to get more insight into the demographics of my speakers. Specifically, I was interested in the time period they lived in and their country of origin. The site listed all the years so I only had to search for each speaker’s country. What I found was that five of the speakers were from the United States, three were from the United Kingdom, one was from Myanmar and one was Australia.
Voyant was the first program used for corpus analysis and I found that it was very easy to use and intriguing. I would definitely agree with Professor Faull in that it is a good entry drug to analyzing a corpus. The friendly colors and interesting graphics made it easy to find some of the more basic patterns in the text. For me it was also useful in that it brought to light some issues I would be facing with my corpus’ dissimilarity in lengths. The book was larger than all the other speeches combined inevitably skewing the data and the smaller, 4 sentence speech had no representation because of how short it was and although it had powerful words, “humanism”,”sex” and “race”, they only appeared once. The best solution I could think of was to run my corpus through voyant with all ten documents and then with the nine smaller document. I also searched the book alone to understand some of the skewing when searching all ten. Of all the features voyant has, the collocation map was by far the most interesting representation of stereotypes and violence against women. I searched certain terms because of a discussion had in class about each gender’s usage of stereotypical words when referring to men and women; I was curious to see if feminist women would have the same trends in the speeches written to battle those stereotypes. It was interesting and a little frightening to see some of the words that came up: women were connected to “emotional”, “Christ”, “kill” and “families” while men are connected to “careers”, “misogyny”, and “sexism”. While women were still connected to “families” and “emotional” the terms for men show the speaker’s indignation and anger with how she is treated by men because of her femininity.
Antconc helped me unpack some of my results a bit more and gave more context and insight. When I used collocation on antconc I continued to see the use of stereotypes in the feminist speeches with phrases like “man predominates” and m en guffawed” versus “women cannot” women forced” “women should”. Anrconc’s way of presenting did show me a change in the manner of speaking based on the times: In the earliest speech, Elizabeth I’s speech to the troops do not have the same tone of fighting for equality. She accepts the stereotype that women are week and feeble and proceeds to say she is different because she had the heart of a king. In other words she is not a good leader generally: she is a good leader because of her masculine qualities that boost her up. She is not strong because women are strong she is strong because she has a man’s strength.
Jigsaw had the potential to work really well for what I needed but I think my corpus would have worked better if it was expanded. I realized very quickly that many of the results I had been getting were only relevant to a specific speech. A speech where the speaker repeated a certain phrase or idea multiple times to drive an idea home but only in one speech. “Opposition” is important in the misogyny speech because Julia Gillard is speaking to the “Leader of the Opposition”, Mr. Slippers (another word that came up on the word clouds) so she says opposition many times, not necessarily in the context someone would expect. Jigsaw also struggled to recognize sentiments in my speeches. None of the speeches were happy but Jigsaw labeled some happier than others.
I think continuing from here I will be expanding my corpus, maybe finding another, more focused list or just adding more speeches to the ones I have now. I was also determining whether or not I should add more of the longer books or if I should remove the one I have now from my corpus.
