This morning the New York Times published a story today about a group of mathematicians who are counting types of words in popular songs in order to get a handle on something like the mood of the country. In trying to data-mine mood, they do what all people who count things do: move from something that you can quantify empirically to something that you can’t. We do this as well when we move from “types of words” or Docuscope strings in Shakespeare plays to “genre.” The strings are empirically countable — they are either there in an established corpus or they aren’t — but one must argue for any connection between what is counted and what such counts represent (genre, mood, etc.). The point I have tried to make on this blog is that the connection is interpretive, and so relies on the hermeneutic skills of the one proposing the link.
In the abstract for the paper, recently published in the Journal of Happiness Studies, they write that: “Among a number of observations, we find that the happiness of song lyrics trends downward from the 1960s to the mid 1990s while remaining stable within genres, and that the happiness of blogs has steadily increased from 2005 to 2009, exhibiting a striking rise and fall with blogger age and distance from the Earth’s equator.” This is an interesting finding, particularly the part about blogger age and distance from the equator. One of the selling-points of their analysis is that the data they have obtained is voluntarily supplied, and so perhaps less subject to the social pressures that accompany surveying. I would want to know, on this score, whether a song-title (for example) is subject to other types of pressures. For example, the songwriter is not just “reporting” an inner state by naming a song in a particular way — take the Ramones song, “I Wanna Be Sedated” for example — but offering this title to an audience. Song-names are rhetorical, and so subject to a different set of pressures than “reporting.” There is another kind of self-interference here that doesn’t seem to be taken into account.
One of the lead researchers on the paper, Peter Sheridan Dodds, argues that data supplied voluntarily on the web can serve as a kind of “remote sensor of well-being.” (I remember hearing similar arguments made about baby names a while back; you don’t have to pay for them and they’re important: therefore they are a good measure of national feeling and trends.) For example, teenagers appear to be the least happy because they more frequently use words such as “sick,” “hate” and “stupid.” Wouldn’t it be more interesting to track how the use of these words (or absence of them) compares to groups of populations that teenagers themselves describe as “unhappy?” My inclination here would be to use data-mining techniques to assay and re-describe classifications made by a given social group in terms that they may not necessarily be aware of. Then the factual claim would be: when teenagers describe someone as happy, that person is x% less likely to use words like “sick,” “hate” and “stupid.”
I can imagine the authors of the Music-Mood study making the following set of claims:
Claim 1) Research on web-logs, lyrics and other sources of expression show that words like “sick,” “hate” and “stupid” occur more frequently in a representative group of works by teenagers. This would be the empirical claim.
Claim 2) People who are experiencing a mood such as “well-being” are less likely to mention words like “sick,” “hate,” and “stupid” in unprompted work such as songwriting or blogging. This is an interpretive claim that must be argued for.
Claim 3) Teenagers are less likely than others to be experiencing a mood of well-being. This is logically true if you accept 1 and 2.
Now, what’s interesting about 2 — the interpretive claim — is that it could be made without numbers. In a sense, you either believe this or you don’t. Which begs the question, what exactly are the numerical claims doing in this argument? What if claim 2 is “kind of true,” or “true only among certain people”? Would this mean that “kind of a lot” of teenagers are unhappy?
I would be more comfortable saying that teenagers use more of the following words (“hate,” “stupid”), and that a close look at the contexts in which they use them (which can never be comprehensive) suggests that their use is connected to mood in the following way (e.g., their use allows teenagers to gain social attention by citing negative emotions, their use indicates depression, their use indexes the presence of Goth subculture, etc.). But I would want to know how the words are used rather than simply making inferences from the fact that they occur. The counter-argument here is that the law of large numbers guarantees that even if there is a wide variation of uses of the words (granting, in effect, that not all occurrences are “reports” of mood), there is nevertheless a broad enough pattern to make a generalization. Fair enough, but what numbers are you going to use to make the generalization?
I’m all for the empirical investigation of abstract concepts like happiness, genre, authorial intent. These higher order concepts don’t come from outer space: we create them to capture some suite of characteristics we find in reality or in ourselves. But the Music-Mood analysis lacks a crucial ingredient: an explicit human judgment about the classes that are being measured by the tokens that are being counted. Unless you make that judgment explicit — saying something like “x% of people who experience what persons y and z would describe as ‘well-being’ also produce unprompted work containing these words — you are really just saying that “a lot” of people who we think are happy do this.
Naming something with a word is a way of creating a class of things (as long as that word is not a proper name), and it is classes of things that are correlated quantitatively using statistics: quantities of classes of words in classes of works, for example. In any such analysis, the classes themselves cannot be derived empirically. They have to be specified in advance by appealing to experience, common sense, expertise, or the like. What troubles me about the Musical Mood analysis here is that the rationale for membership in the class of words indicating “well-being” is not spelled out, and perhaps never could be. I would rather ask someone — an expert? a teenager? — to name people who experience well-being and then do one of Matt Jockers’ most-frequent-word analyses on their lyrics or blogs in order to get at the underlying pattern. It’s fine to begin with a set of words whose occurrence indicates (to you) a feeling 0f well-being, but without knowing quantitatively how indicative they are, the numbers are just another kind of adjective. You might as well read a bunch or web pages and decide for yourself.
My guess is that you would conclude that teenagers write like teenagers rather quickly.