This chapter introduces sentiment analysis as a bridge between language and decision-making, reviewing emotion taxonomies (valence/arousal, Ekman, Plutchik) and core tools (LIWC, ANEW, SentiWordNet) for measuring the sentiment tenor of text. It proposes LiMoLES, a utility function combining monetary payoffs with language-elicited sentiment, and tests it on framing effects in the extreme Dictator Game, showing that human-rated sentiment predicts altruism better than lexicons. The chapter extends LiMoLES to basic emotions, clarifies limits of lexicon intensity and context, and motivates a shift toward normative components (LiMoLNoS) when emotions alone cannot explain choices, ultimately setting up a broader LENS model of emotional and normative influences.