I'm not going to take a strong position on the controversy around Syuzhet here. Ted Underwood made what I thought was a useful point about the issue in his blog post shortly after the controversy began:
All we have is an R package, syuzhet, which does something I would call exploratory data analysis. And it’s hard to evaluate exploratory data analysis in the absence of a specific argument.
For instance, does syuzhet smooth plot arcs appropriately? I don’t know. Without a specific thesis we’re trying to test, how would we decide what scale of variation matters? In some novels it might be a scene-to-scene rhythm; in others it might be a long arc. Until I know what scale of variation matters for a particular question, I have no way of knowing what kind of smoothing is “too much” or “too little.”
The key phrase for me is "exploratory." These methods lead to visualizations that might or might not be interesting; they might or might not tell us something new about novels we (presumably) have already read. I personally am not interested in using these techniques to move categorically towards a "distant reading" paradigm, nor do I think they give us any kind of fundamental truths about literary texts that supersedes understanding derived from actually reading them. At best, these methods piggyback on my existing close reading habits in a kind of hybrid formation.
I take all of this with a grain of salt; it's still pretty fascinating.
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In R Studio, all you have to do is click on "Packages" and then on "Install Packages." You'll have to set a mirror (meaning, the server from which you are actually downloading the files), and R Studio should do the rest.
middlemarch <- get_text_as_string("c:/middlemarch.txt")
sentiment_vector <- get_sentiment(s_v, method="bing")