This Thesis investigates a new measurement technique for emotions. Text mining is used to measure changes in affective content, as well as, in linguistic style in the Enron corpus. LIWC 2007 measures the percentage amount of words that belong to categories associated with emotions and linguistic style. We found a sharp decrease in the intensity of affective content and found little evidence for an emotional dependence on the stock price. Both findings are strongly depended on the frequency used. Two different approaches are conducted for the analysis of linguistic style and both lead to different results. Whereas the first approach shows constancy in the LSM score over the whole time period, the second method fails to find a constant or increasing LSM score. Overall, the new measurement technique is successful in measuring changes in emotions and linguistic style and could lead to stronger results, especially for the LSM score, when a longer time period is considered.

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