RT Article
T1 A Systematic Literature Review of the Use of Computational Text Analysis Methods in Intimate Partner Violence Research
JF Journal of family violence
VO 38
IS 6
SP 1205
OP 1224
A1 Neubauer, Lilly
A1 Straw, Isabel
A1 Mariconti, Enrico
A1 Tanczer, Leonie Maria
A2 Straw, Isabel
A2 Mariconti, Enrico
A2 Tanczer, Leonie Maria
LA English
YR 2023
UL https://krimdok.uni-tuebingen.de/Record/1853375152
AB Purpose: Computational text mining methods are proposed as a useful methodological innovation in Intimate Partner Violence (IPV) research. Text mining can offer researchers access to existing or new datasets, sourced from social media or from IPV-related organisations, that would be too large to analyse manually. This article aims to give an overview of current work applying text mining methodologies in the study of IPV, as a starting point for researchers wanting to use such methods in their own work. Methods: This article reports the results of a systematic review of academic research using computational text mining to research IPV. A review protocol was developed according to PRISMA guidelines, and a literature search of 8 databases was conducted, identifying 22 unique studies that were included in the review. Results: The included studies cover a wide range of methodologies and outcomes. Supervised and unsupervised approaches are represented, including rule-based classification (n = 3), traditional Machine Learning (n = 8), Deep Learning (n = 6) and topic modelling (n = 4) methods. Datasets are mostly sourced from social media (n = 15), with other data being sourced from police forces (n = 3), health or social care providers (n = 3), or litigation texts (n = 1). Evaluation methods mostly used a held-out, labelled test set, or k-fold Cross Validation, with Accuracy and F1 metrics reported. Only a few studies commented on the ethics of computational IPV research. Conclusions: Text mining methodologies offer promising data collection and analysis techniques for IPV research. Future work in this space must consider ethical implications of computational approaches.
K1 Systematic Review
K1 Natural Language Processing
K1 Machine Learning
K1 Text Analysis
K1 Text Mining
K1 Domestic Violence
K1 Intimate Partner Violence
DO 10.1007/s10896-023-00517-7