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This article demonstrated a very practical use for topic modeling by looking at trends in women’s history, attempting to debunk certain myths and popular beliefs. It looked at over half a million abstracts throughout this process, which clearly will provide a lot of data points. An interesting aspect that my colleague  discusses in relation to topic modeling that I hadn’t considered is the issue with specificity, or lack thereof. Especially when only looking at abstracts from these articles, there can be a lack of specificity involved with this analysis. At the same time, a topic modeling analysis looking at the entirety of the articles would be a much more time consuming and expensive process, given the sheer influx of words and data points. I think in certain cases, there can be a tradeoff between specificity with the data and the actual quantity of data that you have to work with. It is up to the analyst as to what he or she values more. In the case of this article, I think that having more data points and only using the abstracts was the correct decision, as the purpose of the article was to conduct an analysis of all of women’s history. Given this, they would likely want to include as many data points as possible.