Interactions are often the part of various complex systems. These interactions lead to various emergent phenomena. The underlying dynamics of these interactions gives rise to interesting patterns which attract a wide range of researchers including medical scientists, data scientists and physicists. Computational study of such a large volume of data through an interdisciplinary approach enables us to assess information, capture the underlying relational patterns between variables and provide deep insight for such systems. Here, computational and statistical findings shed light on the formations and spreading of these phenomena existing across varying disciplines such as conflicts, climate and health and thereby help in inhibiting the growth and framing opinion about the understanding.