Consumers increasingly generate content on social media platforms like Twitter by expressing and discussing their feelings and attitudes, often by using emojis. Brands can take advantage of this vast amount of free and instantly available data by conducting sentiment analyses to monitor their image and to observe consumers’ immediate emotional reactions to marketing activities or brand-related incidents. Until now, emojis were mostly ignored in these analyses. An online experiment with 1,765 participants indicates that an inclusion of emojis can improve the correct emotional interpretation of brand-related tweets (study 1). A comparison of six different sentiment analysis tools then identifies the tools that are most suitable to analyze the polarity as well as the emotional category of brand-related tweets containing emojis (study 2). Study 3 describes the development of an emoji lexicon for sentiment analyses based on a qualitative study (3a) with 1,157 participants and a quantitative study (3b) with 1,926 participants. Study 4 confirms the hypothesis that an inclusion of emojis translated with the lexicon leads to a significantly higher number of correctly classified tweets with respect to valence as well as emotion category in automated sentiment analyses of brand-related tweets. Then. by combining the tools identified in study 2 and the lexicon developed in study 3, sentiment values for 14 different global brands from four product categories are determined by analyzing 6,053,288 user-generated tweets (study 5). The results show that an inclusion of emojis in the sentiment analysis of brand-related tweets is more important for hedonic than utilitarian product categories. Finally, a management tool to continuously monitor mood towards a brand with social media data is developed. The reliability of the presented method is verified with an exemplary comparison of peaks and troughs in the measured sentiment values to brand-related incidents from the evaluation period.