All of us aspire to have a good life and to be happy. Yet, how do we know whether people reach this goal and are satisfied with their lives? We know that satisfaction with life is driven by more than just money. Building blocks such as social relationships, job satisfaction, health, level of education and safety, play an essential role. People satisfied with their lives are generally more productive and caring members of society. Therefore, maximising life satisfaction is often the ultimate goal of governments and policymakers. Previously, we relied on survey data, released after a significant time lag, to inform us how satisfied people are with their lives. However, we need data that reflect the “present” rather than survey data’s “past” findings in an ever faster changing world. In the form of Big Data, real-time data allows us to collect information from social media platforms. We can now “listen” to individuals and nations and analyse the sentiment of their written word. Subsequently, we extract a live stream of tweets and use machine learning to analyse the tweets’ sentiment and underlying emotions. Once the tweets are classified as having a positive or negative sentiment, we derive a balance score. This allows us . The measure gives researchers and policymakers an unprecedented insight into human behaviour, allowing significant predictive powers and fast affirmative policy action.