Recent work shows that people are not solely motivated by the economic consequences of the available actions, but they also have moral preferences for ` doing the right thing ' , independently of its economic consequences. Here we add to this literature with two experiments. In Study 1 (N=567) we implement an extreme dictator game in which dictators either get \0.50 and another person gets nothing, or the other way around (i.e., the other person gets \0.50 and the dictator gets nothing). We experimentally manipulate the words describing the available actions using six words, from very negative (e.g., stealing) to very positive (e.g., donating) connotations. Our hypothesis is that people are reluctant to make actions described using words with a negative connotation, and are eager to make actions described using words with a positive connotation, independently of their economic consequences. As predicted, we find that the connotation of the word has a U-shaped effect on pro-sociality . Moreover, we show that the overall pattern of results, the U-shape, but not its details, can be explained using a technique from Computational Linguistics known as Sentiment Analysis . In Study 2 (N=413, pre-registered) we make a step forward and we collect the self-reported moral judgment and feeling associated to each of the six words used in Study 1. We show that the rate of pro-sociality in Study 1 can be predicted from the moral judgments and the feelings in Study 2 via Krupka \& Weber's utility function. In sum, our findings provide additional evidence for the existence and relevance of moral preferences, confirm the usefulness of Krupka \& Weber's utility function, and suggest that building bridges from computational linguistics to behavioral science can contribute to our understanding of human decision making .
Recent work suggests that people are not solely motivated by the economic consequences of the available actions, but they also have moral preferences for " doing the right thing " , independently of its economic consequences. However, it remains unclear in what situations moral preferences can be activated by simply changing the framing of a decision problem. For example, earlier work proposed that moral preferences can account for framing effects in the Dictator game. However, more recent work has casted doubts on the very existence of framing effects in this game. Here we shed light on this point with two experiments. In Study 1 (N=567) we implement an extreme Dictator game in which dictators either get \0.50 and another person gets nothing, or the opposite (i.e., the other person gets \0.50 and the dictator gets nothing). We experimentally manipulate the words describing the available actions using six words, from very negative (e.g., stealing) to very positive (e.g., donating) connotations. As we predicted, we find that the rate of pro-sociality is affected by the words used to describe the available actions . In Study 2 (N=413, pre-registered) we collect the self-reported moral judgment and feeling associated to each of the six words used in Study 1. We show that these moral judgments and feelings can explain the framing effects in Study 1. In sum, we find that changing only one word in the instructions of an extreme Dictator game can alter people's behavior, and that behavioral changes can be explained using moral judgments and feelings associated to these words .
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However, it remains unclear in what situations moral preferences can be activated by simply changing the framing of a decision problem. For example, earlier work proposed that moral preferences can account for framing effects in the Dictator game. However, more recent work has casted doubts on the very existence of framing effects in this game. Here we shed light on this point
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Our hypothesis is that people are reluctant to make actions described using words with a negative connotation, and are eager to make actions described using words with a positive connotation, independently of their economic consequences. As
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connotation of the word has a U-shaped effect on
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. Moreover, we show that the overall pattern of results, the U-shape, but not its details, can be explained using a technique from Computational Linguistics known as Sentiment Analysis
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the rate of pro-sociality in Study 1 can be predicted from the
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the feelings in Study 2 via Krupka \& Weber's utility function.
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our findings provide additional evidence for the existence and relevance of moral preferences, confirm the usefulness of Krupka \& Weber's utility function, and suggest that building bridges from computational linguistics to behavioral science can contribute to our understanding of human decision making
we find that changing only one word in the instructions of an extreme Dictator game can alter people's behavior, and that behavioral changes can be explained using moral judgments and feelings associated to these words