Hate speech, machine classification and statistical modelling of information flows on Twitter: interpretation and communication for policy decision making

In 2013, the murder of Drummer Lee Rigby in Woolwich, UK led to an extensive public social media reaction. Given the extreme terrorist motive and public nature of the actions it was feasible that the public response could include written expressions of hateful and antagonistic sentiment towards a particular race, ethnicity and religion, which can be interpreted as ‘hate speech’. This provided motivation to study the spread of hate speech on Twitter following such a widespread and emotive event. In this paper we present a supervised machine learning text classifier, trained and tested to distinguish between hateful and/or antagonistic responses with a focus on race, ethnicity or religion; and more general responses. We used human annotated data collected from Twitter in the immediate aftermath of Lee Rigby’s murder to train and test the classifier. As “Big Data” is a growing topic of study, and its use is in policy and decision making is being constantly debated at present, we discuss the use of supervised machine learning tools to classify a sample of “Big Data”, and how the results can be interpreted for use in policy and decision making. The results of the classifier are optimal using a combination of probabilistic, rule-based and spatial based classifiers with a voted ensemble meta-classifier. We achieve an overall F-measure of 0.95 using features derived from the content of each tweet, including syntactic dependencies between terms to recognise “othering” terms, incitement to respond with antagonistic action, and claims of well founded or justified discrimination against social groups. We then demonstrate how the results of the classifier can be robustly utilized in a statistical model used to forecast the likely spread of hate speech in a sample of Twitter data

Selected Computing Research Papers Volume 5 June 2016

An Analysis of Current Computer Assisted Learning Techniques Aimed at Boosting Pass Rate Level and Interactivity of Students (Gilbert Bosilong) ........................................ 1 Evaluating the Ability of Anti-Malware to Overcome Code Obfuscation (Matthew Carson) .................................................................................................................................. 9 Evaluation of Current Research in Machine Learning Techniques Used in Anomaly-Based Network Intrusion Detection (Masego Chibaya) ..................................................... 15 A Critical Evaluation of Current Research on Techniques Aimed at Improving Search Efficiency over Encrypted Cloud Data (Kgosi Dickson) ........................................ 21 A Critical Analysis and Evaluation of Current Research on Credit Card Fraud Detection Methods (Lebogang Otto Gaboitaolelwe) .......................................................... 29 Evaluation of Research in Automatic Detection of Emotion from Facial Expressions (Olorato D. Gaonewe) ......................................................................................................... 35 A Critical Evaluation on Methods of Increasing the Detection Rate of Anti-Malware Software (Thomas Gordon) ................................................................................................ 43 An Evaluation of the Effectiveness of the Advanced Intrusion Detection Systems Utilizing Optimization on System Security Technologies (Carlos Lee) ............................ 49 An Evaluation of Current Research on Data Mining Techniques in Decision Support (Keamogetse Mojapelo) ...................................................................................................... 57 A Critical Investigation of the Cognitive Appeal and Impact of Video Games on Players (Kealeboga Charlie Mokgalo) ................................................................................ 65 Evaluation of Computing Research Aimed at Improving Virtualization Implementation in the Cloud (Keletso King Mooketsane) ................................................. 73 A Critical Evaluation of the Technology Used In Robotic Assisted Surgeries (Botshelo Keletso Mosekiemang) ....................................................................................... 79 An Evaluation of Current Bio-Metric Fingerprint Liveness Detection (George Phillipson) ........................................................................................................................... 85 A Critical Evaluation of Current Research into Malware Detection Using Neural-Network Classification (Tebogo Duduetsang Ramatebele) ................................................ 91 Evaluating Indirect Detection of Obfuscated Malware (Benjamin Stuart Roberts) ......... 101 Evaluation of Current Security Techniques for Online Banking Transactions (Annah Vickerman) ....................................................................................................................... 10