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In The Digital Humanities Contribution to Topic Modeling, I found it interesting how much the authors stress the importance of humanist’s role in topic modeling. Due to the availability and magnitude of text data in recent years topic modeling has exploded with popularity. Because topic models work by consuming vast amounts or corpus of text, the results of topic models are generally widespread or blanket statements about the data itself. For this reason I agree with the authors that understanding how these methods work is critical. However, is it really enough to understand the inner workings of the algorithm alone?

Meeks and Weingart believe that in some cases the debate surrounding topic models is too concerned with the success of the algorithm itself opposed to the human space that the algorithm is working in. As a field, topic modelers have become obsessed with understanding the strengths and weaknesses of the topic models that they lost focus on what is really important, interpreting language.

This point of contention will be difficult for researchers to balance in the future. Society rewards speed and profit making it difficult to ensure that our models are not only accurate but ethical. My hope is that humanists and computer scientists will work together to make topic models more accurate and it turn less futile.

In SJ’s reading response, he/she brings up a very compelling argument against topic models, which is that sheer abundance of word count should be mistaken for abundance of meaning. Language and text are not always exact science but also art. There is certainly room for human emotion within a text and I agree with SJ in that sometimes these emotions can trump frequency.