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Topic modeling is an important field that will allow computer programs to better analyze and synthesize categorical data. While the programs we have right now aren’t perfect, they’re improving with machine learning and our understanding of their code increases over time. In “The Digital Humanities Contribution to Topic Modeling” Elijah Meeks and Scott Weingart argue that the tools we have at our disposal are too blunt at the moment for them to be taken seriously. While I agree with this sentiment, I don’t believe we should give up on the whole field just because they haven’t produced a perfect finished product yet. I also disapprove of their writing style, because the complexity of the words they used distracted me from the content of the piece.

EC said in the post “Can the Humanities Topic Model?” that we should remember that topic modeling is just a tool to help us, and shouldn’t be the only thing we use to analyze the works in the humanities. We shouldn’t allow ourselves to become too dependent on computers and programs to do our work for us, and this is a great example of where we have more knowledge about something than a computer does, at least for the moment.