Extracting Actionable Knowledge from Domestic Violence Discourses on Social Media

Abstract

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.

How to be Helpful on Online Support Forums?

“…Helpfulness on Online Support Communities Helpfulness has been studied in online support communities where peers can offer help and support to one another. These communities often center around a shared life situation such as chronic health conditions (Subramani and O'Connor, 2018;Green et al, 2020) and family bereavement (Schotanus-Dijkstra et al, 2014;Paulus and Varga, 2015). Several factors were emphasized in common: Peers were found more helpful when they are emotionally warm and compassionate, give others choice on a solution, willing to accept others' perspectives and experiences, practice active listeningby paraphrasing, asking questions and reflecting feelings, give pertinent advice/insights to help others to solve their problem, as well as share similar experiences (Chuang and Yang, 2012;Schotanus-Dijkstra et al, 2014;Paulus and Varga, 2015;Subramani and O'Connor, 2018;McKiernan et al, 2018;Green et al, 2020).…”

“…Helpfulness has been extensively studied based on exchanges in online support communities (Chuang and Yang, 2012; Schotanus-Dijkstra et al, 2014; Paulus and Varga, 2015;Subramani and O'Connor, 2018;McKiernan et al, 2018;Green et al, 2020). These studies found that helpfulness is associated with various characteristics such as emotional warmth, relevant knowledge, willingness to understand, empowering choice, active listening as well as sharing of similar experiences.…”

From Networking to Mitigation: The Role of Social Media and Analytics in Combating the COVID-19 Pandemic

“…In the U.S., 20 people suffer from DV every minute. The consequences of DV for victims are often severe, far-reaching, and long-lasting, causing major health (including both physical and mental health), welfare, and economic damages (Subramani, 2019). DV is the 12th leading cause of years of life lost.…”

Extracting Actionable Knowledge From Social Networks Using Structural Features

“…Subramani et al proposed a novel framework in [10] to model and discover different types of domestic violence in the public domain and ultimately provide actionable knowledge. Their method uses topic detection to turn Twitter data into actionable knowledge.…”