Veracity Analysis and Prediction in Social Big Data

In big data sector, social media plays an important role for providing the biggest amount of unstructured data. Twitter is one such social media platform for dissipating unverified information during the time of disaster like cyclones, earthquake and flood. Veracity is the degree to which the information is accurate and trusted. The main objective of this paper is to identify the veracity of the rumour and find the source of the rumour. The authors analyse the PHEME data set in which the Sydneysiege event is chosen for analysis. This paper proposes a novel and hybrid rumour source–detector approach which combines the merits of graph and tree data structures. It identifies the source node traversing through general tree and predicts the rumour-spreading possibilities with general graph using spanning tree.