The use of social networks has been shown as a powerful tool for driving populations opinions towards specific trends and interests. Yet what actually makes the success of a profile? Are emotions responsible for driving the public opinion and the opinion of the followers? We present a study on the influence of emotions in their success. To do so, we first created a novel dataset called InfluEmo, crawled from Instagram, in which we designed and analyzed the impact of emotions in influencers’ success. The dataset InfluEmo is novel and freely available. Automatic emotion extraction yielded promising results, supporting our hypothesis that specific emotional profiles in influencers’ posted content are associated with measurable indicators of success measured as number of followers. These findings suggest that emotions might play a systematic and quantifiable role in shaping public opinion and influencing users’ interactions on Instagram. Using the novel InfluEmo dataset (≈38,000 posts, ≈970 profiles, 4 domains: fashion, climate, AI, and journalism), the paper shows, in fact, that more positive emotional language is consistently associated with higher engagement, with fashion influencers achieving the highest average likes (≈138,885/post) and lowest emotional entropy, while AI, climate, and journalism content—characterized by more neutral or mixed emotions—exhibits lower likes (≈6761–19,544/post), weaker sentiment–likes correlations, and higher entropy, indicating that positivity and emotional predictability outperform informational complexity in driving Instagram success.