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Topic modeling is a method used by programmers to analyze a large number of documents or text files. The documents are first manipulated to fix possible errors and make it easier for the computer. For example, all words are lowercased, punctuation is removed, and the tense of all words may be changed to a single form. This removes possible human errors in capitalization,  punctuation, and other categories. Meeks and Weingart argue that current topic modeling methods haven’t yet been perfected and for this reason shouldn’t be used in analysis. But, I agree with HC when they say that they “don’t believe we should give up on the whole field just because they haven’t produced a perfect finished product yet,” as there are many things in the computer world which aren’t yet flawless. For example, many companies use artificial intelligence for different aspects of products and business. Although artificial intelligence is nowhere near perfected, it constantly produces useful results for companies and consumers.