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Psychologists have long debated whether it is possible to assess how people subjectively feel without asking them. The recent proliferation of online social networks has recently added a fresh chapter to this discussion, with research now suggesting that it is possible to index people's subjective experience of emotion by simply counting the number of emotion words contained in their online social network posts. Whether the conclusions that emerge from this work are valid, however, rests on a critical assumption: that people's usage of emotion words in their posts accurately reflects how they feel. Although this assumption is widespread in psychological research, here we suggest that there are reasons to challenge it. We corroborate these assertions in 2 ways. First, using data from 4 experience-sampling studies of emotion in young adults, we show that people's reports of how they feel throughout the day neither predict, nor are predicted by, their use of emotion words on Facebook. Second, using simulations we show that although significant relationships emerge between the use of emotion words on Facebook and self-reported affect with increasingly large numbers of observations, the relationship between these variables was in the opposite of the theoretically expected direction 50% of the time (i.e., 3 of 6 models that we performed simulations on). In contrast to counting emotion words, we show that judges' ratings of the emotionality of participants' Facebook posts consistently predicts how people feel across all analyses. These findings shed light on how to draw inferences about emotion using online social network data.

Psychologists have long debated whether it is possible to assess how people subjectively feel without asking them. The recent proliferation of online social networks has recently added a fresh chapter to this discussion, with research now suggesting that it is possible to index people's subjective experience of emotion by simply counting the number of emotion words contained in their online social network posts. Whether the conclusions that emerge from this work are valid, however, rests on a critical assumption: that people's usage of emotion words in their posts accurately reflects how they feel. Although this assumption is widespread in psychological research, here we suggest that there are reasons to challenge it. We corroborate these assertions in 2 ways. First, using data from 4 experience-sampling studies of emotion in young adults, we show that people's reports of how they feel throughout the day neither predict, nor are predicted by, their use of emotion words on Facebook. Second, using simulations we show that although significant relationships emerge between the use of emotion words on Facebook and self-reported affect with increasingly large numbers of observations, the relationship between these variables was in the opposite of the theoretically expected direction 50% of the time (i.e., 3 of 6 models that we performed simulations on). In contrast to counting emotion words, we show that judges' ratings of the emotionality of participants' Facebook posts consistently predicts how people feel across all analyses. These findings shed light on how to draw inferences about emotion using online social network data.