Malicious Interlocutor Detection Using Forensic Analysis of Historic Data

The on-going problem of child grooming online grows year on year and whilst government legislation looks to combat the issue by levying heavier penalties on perpetrators of online grooming, crime figures still increase. Government guidance directed towards digital platforms and social media providers places emphasis on child safety online. As this research shows, government initiatives have proved somewhat ineffective. Therefore, the aim of this research is to investigate the scale of the of the problem and test a variety of machine learning and deep learning techniques that could be used in a novel intelligent solution to protect children from online predation. The heterogeneity of online platforms means that a one size fits all solution presents a complex problem that needs to be solved. The maturity of intelligent approaches to Natural Language Processing makes it possible to analyse and process text data in a wide variety of ways. Pre-processing data enables the preparation of text data in a format that machines can understand and reason about without the need for human interaction. The on-going development of Machine Learning and Deep Learning architectures enables the construction of intelligent solutions that can classify text data in ways never imagined. This thesis presents research that tests the application of potential intelligent solutions such as Artificial Neural Networks and Machine Learning algorithms applied in Natural Language Processing. The research also tests the performance of pre-processing workflows and the impact of pre-processing of both online grooming and more general chat corpora. The storage and processing of data via a traditional relational database management system has also been tested for suitability when looking to detect grooming conversation in historical data. The on-going development of Machine Learning and Deep Learning architectures enables the construction of intelligent solutions that can classify text data in ways never imagined. This thesis presents research that tests the application of potential intelligent solutions such as Artificial Neural Networks and Machine Learning algorithms applied in Natural Language Processing. The research also tests the performance of pre-processing workflows and the impact of pre-processing of both online grooming and more general chat corpora. The storage and processing of data via a traditional relational database management system has also been tested for suitability when looking to detect grooming conversation in historical data. Document similarity measures such as Cosine Similarity and Support Vector Machines have displayed positive results in identifying grooming conversation, however, a more intelligent solution may prove to have better currency in developing a smart autonomous solution given the ever-evolving lexicon used by participants in online chat conversations

Disclosing Extra-Dyadic Involvement (EDI): Understanding Attitudes, Subjective Norms, and Perceived Behavioral Control

Extra-dyadic involvement (EDI) is a complex issue that affects many individuals, couples, and families. One important, relatively unexplored issue concerns the disclosure of EDI. Despite some scholarly discourse on whether disclosure should be facilitated in a therapeutic context (e.g., Butler et al. in J Marital Fam Ther 35:125–143, 2009; Butler et al. in Am J Fam Ther 36:265–283, 2008), empirical research has not studied the intrapersonal or interpersonal processes related to disclosure. In this study, we explored potential factors involved in the decision to disclose EDI by looking at the relationships among attitudes towards EDI (in terms of perceived justifications and costs), subjective norms (obligation to disclose), and perceived behavioral control (difficulty) associated with EDI disclosure. Our sample included 337 individuals enrolled in at least one university course at one of three geographically distinct universities. Findings indicate that more permissive attitudes towards EDI are not significantly associated to the perceived difficulty in disclosing EDI or the obligation associated with disclosing EDI involving sexual intercourse. However, more permissive attitudes are related to lower felt obligation to disclose EDI that does not involve direct sexual intercourse. Conversely, more restrictive attitudes towards EDI (perceived severity, degree of perceived upset, and how detrimental it is perceived to be to the relationship) predicted greater difficulty but also greater obligation in disclosing all forms of EDI. Specific implications of these findings, including potential implications for therapy, are discussed. Overall, this study provides preliminary information regarding potentially useful factors to consider in understanding the EDI disclosure process that may also be useful in developing intervention points in therapy

SafeChat System with Natural Language Processing and Deep Neural Networks

The internet plays an ever-increasing part in the day-to-day lives of many people. Ubiquitous computing has given rise to sophisticated, streamlined and faster connections across a range of devices. Mobile smart phones are in the hands of children as young as five years old, and whilst this allows them to interact with educational applications and the wealth of information available on-line, it can put them in danger. There has been a consistent stream of stories involving children and adolescents being at risk because of unsafe on-line behaviour. Predators can prey on the vulnerable, by pretending to be a peer and convincing them, by charm or threats, to compromise their safety. Governments across the globe have initiatives to combat this threat, there are working groups and police task forces in place to respond to both the growing number, and impact of these incidents on children, young people, families and communities. In order to monitor on-line conversation and identify different levels of threats, the SafeChat system was designed and implemented using an ontology-based system and Natural Language Processing (NLP) techniques

Attachment-Related Dynamics During a Positively Themed Couple Interaction: Implications of Anxiety and Avoidance.

Attachment style and adult intimate relationships have often been studied in the context of distress, such as couple conflict. Attachment anxiety represents an intense need for closeness and reassurance based on fears of abandonment, while attachment avoidance is typified by discomfort with emotional closeness and intimacy. Understanding these attachment-related processes in couples is important, although little research has looked at these dynamics in the context of positively themed interactions, where relational distress is much lower. In this study, we examined the interactions of 63 couples to understand the relationship between attachment style (anxiety and avoidance) and feelings toward partner, psychophysiological arousal, and linguistic process (positive, negative, and “we” language). The interaction was a discussion that commonly occurs in some form in couple therapy: how the couple met. Results revealed both men and women higher in attachment anxiety felt more positively toward their partner during the interaction. However, women with a male partner higher in attachment anxiety had higher levels of psychophysiological distress during the interaction. We also discovered a systemic relationship between anxiety and avoidance, with individuals higher in anxiety using more negative and less “we” language during the interaction, but only if their partners were higher in avoidance. Other findings involving age, gender, education status, income, individual distress, and relationship status were also found in the context of these positively themed interactions. We discuss implications of the findings for clinicians as well as future research needed to clarify and build upon our current findings

Evaluating the Relationship Between Family Resilience and Grief-Related Symptoms: A Preliminary Analysis

Walsh’s Family Resilience Framework offers clinicians a comprehensive theoretical approach for supporting bereaved families. In this study, a total of 139 bereaved adults who lost a family member in the last 5 years were surveyed about their family’s resilience processes, their current outlook on life, and their current grief-related symptoms. The data from this sample were analyzed using confirmatory factor analysis and structural regression. Family resilience processes were negatively related to grief symptoms; however, this relationship was mediated by personal meaning. The results suggest that Walsh’s Family Resilience Framework may be an appropriate conceptual tool to assess family resilience in bereavement practice

Couple Emotional Experience: Effects of Attachment Anxiety in Low and High Structure Couple Interactions

This study used data from 63 heterosexual couples to investigate the effects of attachment anxiety and how they relate to emotional experience (i.e. psychophysiological distress and feelings towards a partner) in the context of two therapy-like conditions (low and high structure). We examined both the effect of an individual\u27s anxiety on his/her own emotional experience (actor effects) and on the partner\u27s experience (partner effects). During both interactional conditions, female partners of men higher in attachment anxiety experienced greater psychophysiological distress. In addition, men and women higher in attachment anxiety were not significantly different from others in terms of their feelings towards their partner during the low structure condition. However, their feelings were significantly more positive than others during the high structure condition, providing some evidence that attachment-based interventions can be especially useful for clients higher in attachment anxiety