2 research outputs found
Extracting Actionable Knowledge from Domestic Violence Discourses on Social Media
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
A Survey on Actionable Knowledge
Actionable Knowledge Discovery (AKD) is a crucial aspect of data mining that
is gaining popularity and being applied in a wide range of domains. This is
because AKD can extract valuable insights and information, also known as
knowledge, from large datasets. The goal of this paper is to examine different
research studies that focus on various domains and have different objectives.
The paper will review and discuss the methods used in these studies in detail.
AKD is a process of identifying and extracting actionable insights from data,
which can be used to make informed decisions and improve business outcomes. It
is a powerful tool for uncovering patterns and trends in data that can be used
for various applications such as customer relationship management, marketing,
and fraud detection. The research studies reviewed in this paper will explore
different techniques and approaches for AKD in different domains, such as
healthcare, finance, and telecommunications. The paper will provide a thorough
analysis of the current state of AKD in the field and will review the main
methods used by various research studies. Additionally, the paper will evaluate
the advantages and disadvantages of each method and will discuss any novel or
new solutions presented in the field. Overall, this paper aims to provide a
comprehensive overview of the methods and techniques used in AKD and the impact
they have on different domains