The study of large-scale socially relevant datasets using Network Theory based data analysis and computational modelling approaches yield unprecedented insight into human sociality and social/societal structures and behavioural processes. This is well-demonstrated by our analysis of large mobile phone dataset, confirming the Granovetterian picture of social networks being modular, having communities with strong internal ties and linked with weaker external ties {1}. As the data also includes mobile phone users’ demographics, i.e. gender and age, we have studied the nature of human social interactions from Dunbarian egocentric viewpoint and got a deeper insight into the gender and age-related social behaviour patterns and dynamics of human relationships, across their lifespan {2}. With the help of open geophysical (sunrise, sunset, length of daylight), seasonal (daily temperature) and geographical (population distribution) data, we investigated the influence of seasonality and geographical location on human activity patterns, observing two daily inactivity/resting periods, such that the nocturnal resting period is influenced by the length of daylight and latitudinal location the person lives, and the afternoon resting period by the temperature, and that the afternoon and nocturnal resting periods appear to be counterbalancing each other {3,4}. To get deeper understanding of the above-described phenomena, the next step is to develop models of human sociality, social/societal networks and processes of their formation and information spreading. One of our models, based on network sociology mechanisms for making friends, produced many empirically observed Granovetterian features of social networks, such as meso- scale community and macro-scale topology formation {5,6}. In subsequent models we investigated the roles of social networks being layered, multiplexing or context based, geography dependent, and having relationships between people changing in time. In sum, the large-scale data-driven analytics and modelling approaches to social systems opens up an unprecedented perspective to gain understanding of human sociality from individual to societal level, which with the availability of various socially relevant datasets and development of computational methodologies could lead to tools of social and societal design.