  Domestic Violence (DV) is considered as big social issue and there exists a
strong relationship between DV and health impacts of the public. Existing
research studies have focused on social media to track and analyse real world
events like emerging trends, natural disasters, user sentiment analysis,
political opinions, and health care. However there is less attention given on
social welfare issues like DV and its impact on public health. Recently, the
victims of DV turned to social media platforms to express their feelings in the
form of posts and seek the social and emotional support, for sympathetic
encouragement, to show compassion and empathy among public. But, it is
difficult to mine the actionable knowledge from large conversational datasets
from social media due to the characteristics of high dimensions, short, noisy,
huge volume, high velocity, and so on. Hence, this paper will propose a novel
framework to model and discover the various themes related to DV from the
public domain. The proposed framework would possibly provide unprecedentedly
valuable information to the public health researchers, national family health
organizations, government and public with data enrichment and consolidation to
improve the social welfare of the community. Thus provides actionable knowledge
by monitoring and analysing continuous and rich user generated content.
