We performed quantitative analysis on transcriptions of 784 interviews with Holocaust survivors. The interviews were collected by the University of Southern California Shoah Foundation, and the first 15 minutes of each interview had been transcribed using automatic speech recognition. The survivors were an aging population as the interviews were conducted around fifty years after the end of the Holocaust. We used statistical methods and algorithms to analyze the data including keyness analysis, topic modeling, and emotionality analysis. We used the Contemporary Corpus of American English (COCA) as a comparative corpus for these analyses. Overall, we found that survivors prioritized themes of the Holocaust and their families in the interviews. Specific words and themes reoccurred across the corpus demonstrating a collective and consistent memory of trauma. Our emotionality analyses revealed that survivors used slightly more positive language and fewer words relating to anger, disgust, and fear than the speakers in our comparative corpus. / Thesis / Master of Science (MSc) / For this thesis, we analyzed 784 transcribed interviews with Holocaust survivors. The interviews were conducted by the Shoah Foundation and took place from 1994-2000; around 50 years after the end of World War II. We compared the language in the interviews to the spoken component of a large corpus (collection of texts) called The Contemporary Corpus of American English (COCA). In our analyses, we found the words that are most representative of the survivors' language across the corpus. We also found topics that were discussed most frequently in the interviews. Words and topics relating to family, Judaism, and experiences of the Holocaust were the most common. We also analyzed the emotionality of the survivors' language and found that overall, they used slightly more positive words than the words in COCA. They also used fewer words associated with the emotions anger, fear, and disgust.
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/29060 |
| Date | January 2023 |
| Creators | Altman, Emilie |
| Contributors | Kuperman, Victor, Cognitive Science of Language |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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