Child abuse and domestic abuse: Content and feature analysis from social media disclosures

Sudha Subramani, Hua Wang, Md Rafiqul Islam, Anwaar Ul-Haq, Manjula O'Connor

Research output: Book chapter/Published conference paperConference paper

3 Citations (Scopus)

Abstract

Due to increase in popularity of social media, people have started discussing their thoughts and opinions in the form of textual posts. Currently, the people tend to disclose even the socially tabooed topics such as Child Abuse (CA), and Domestic Abuse (DA) to receive the desired response and social support in turn. The increasing volume of abuse related posts being shared on social media is of great interest for public health sectors and family welfare organizations to monitor the public health and promote support services. However, due to the large volume, high velocity and huge variety of context and content of user generated data, it is difficult to mine the different kinds of abuse (CA and DA) related posts from other general posts, that flood over the web. Hence, this paper aims to discover and differentiate the characteristics of CA and DA posts from the massive user generated posts, with the underlying context. Various features such as psycholinguistic, textual and sentimental features are analyzed and Machine Learning techniques are trained to analyze the predictive power of extracted features. Hence, the resulting model achieves more predictive power with high accuracy in classifying possible cases of abuse related posts from diverse user posts.
Original languageEnglish
Title of host publicationDatabases theory and applications
Subtitle of host publication29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, May 24-27, 2018, proceedings
EditorsJunhu Wang, Cong Gao, Jinjun Chen, Jianzhong Qi
Place of PublicationChampagne, Switzerland
PublisherSpringer
Chapter14
Pages174-185
Number of pages12
Volume10837
ISBN (Electronic)9783319920139
ISBN (Print)9783319920122
DOIs
Publication statusPublished - 2018
Event29th Australasian Database Conference - Griffith University, Gold Coast, Australia
Duration: 24 May 201827 May 2018
http://www.ict.griffith.edu.au/conferences/adc2018/

Conference

Conference29th Australasian Database Conference
CountryAustralia
CityGold Coast
Period24/05/1827/05/18
OtherThe Australasian Database Conference series is an annual forum for sharing the latest research progresses and novel applications of database systems, data driven applications and data analytics for researchers and practitioners in these areas from Australia, New Zealand and in the world. The 29th edition of the Australasian Database Conference, ADC 2018, will be co-located with 23rd International Conference on Database Systems For Advanced Applications (DASFAA 2018) in Gold Coast, Australia. ADC 2018 will be a key event of the 4-day Australasian Database Research Week. In addition to regular research papers, industry papers, demo sessions, and plenary poster sessions, ADC 2018 will also feature multiple keynote speeches and tutorials given by world-leading researchers and industry leaders.
Internet address

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  • Cite this

    Subramani, S., Wang, H., Islam, M. R., Ul-Haq, A., & O'Connor, M. (2018). Child abuse and domestic abuse: Content and feature analysis from social media disclosures. In J. Wang, C. Gao, J. Chen, & J. Qi (Eds.), Databases theory and applications: 29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, May 24-27, 2018, proceedings (Vol. 10837, pp. 174-185). Springer. https://doi.org/10.1007/978-3-319-92013-9_14