Atribuição de autoria em micro-mensagens

Orientadores: Ariadne Maria Brito Rizzoni Carvalho, Anderson de Rezende RochaDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação CientíficaResumo: Com o crescimento continuo do uso de midias sociais, a atribuição de autoria tem um papel imortante na prevenção dos crimes cibernéticos e na análise de rastros online deixados por assediadores, \textit{bullies}, ladrões de identidade entre outros. Nesta dissertação, nós propusemos um método para atribuição de autoria que é de cem a mil vezes mais rápido que o estado da arte. Nós também obtivemos uma acurácia 65\% na classificação de 50 autores. O método proposto se baseia numa representação de caracteristicas escalável utilizando os padrões das mensagens dos micro-blogs, e também nos utilizamos de um classificador de padrões customizado para lidar com grandes quantidades de dados e alta dimensionalidade. Por fim, nós discutimos a redução do espaço de busca na análise de centenas de suspeitos online e milões de micro mensagens online, o que torna essa abordagem valiosa para forense digital e aplicação das leisAbstract: With the ever-growing use of social media, authorship attribution plays an important role in avoiding cybercrime, and helping the analysis of online trails left behind by cyber pranks, stalkers, bullies, identity thieves and alike. In this dissertation, we propose a method for authorship attribution in micro blogs with efficiency one hundred to a thousand times faster than state-of-the-art counterparts. We also achieved a accuracy of 65% when classifying texts from 50 authors. The method relies on a powerful and scalable feature representation approach taking advantage of user patterns on micro-blog messages, and also on a custom-tailored pattern classifier adapted to deal with big data and high-dimensional data. Finally, we discuss search space reduction when analysing hundreds of online suspects and millions of online micro messages, which makes this approach invaluable for digital forensics and law enforcementMestradoCiência da ComputaçãoMestre em Ciência da Computaçã

An Overview of Forensic Linguistics and its Application in Real-Life Cases

Treballs Finals del Grau d'Estudis Anglesos, Facultat de Filologia, Universitat de Barcelona. Curs: 2022-2023. Tutora: Núria Gavaldà[eng] Forensic linguistics is an emerging multidisciplinary field within applied linguistics that focuses on the various intersections between language and law. To ensure a fair and effective legal process, it is crucial to have an understanding of linguistic principles in order to avoid misinterpretations or misunderstandings. This study provides a general overview of the expansive field of forensic linguistics and highlights its diverse contributions to the criminal justice system. It provides a summary of prominent legal cases and analyses the intersection between forensic linguistics and applied linguistics. Therefore, this end-of-degree paper aims to demonstrate how this field of linguistics can play a key role when it comes to solving legal cases. To develop such analysis, this investigation will be making reference to multiple distinguished forensic linguists and their involvement in solving legal and criminal cases.[cat] La lingüística forense és un camp multidisciplinari emergent dins de la lingüística aplicada que se centra en les diferents interseccions entre la llengua i el dret. Per garantir un procés legal just i eficaç, és crucial tenir una comprensió dels principis lingüístics per evitar interpretacions errònies o malentesos. Aquest estudi ofereix una visió general de l'ampli camp de la lingüística forense i destaca les seves diverses contribucions al sistema de justícia penal. Ofereix un resum de casos legals destacats i analitza la intersecció entre la lingüística forense i la lingüística aplicada. Per tant, aquest treball de fi de grau pretén demostrar com aquest àmbit de la lingüística pot tenir un paper clau a l'hora de resoldre casos judicials. Per desenvolupar aquesta anàlisi, aquesta investigació farà referència a múltiples lingüistes forenses distingits i la seva implicació en la resolució de casos legals i penals

Authorship Authentication for Twitter Messages Using Support Vector Machine

With the rapid growth of internet usage, authorship authentication of online messages became challenging research topic in the last decades. In this paper, we used a team of support vector machines to authenticate 5 Twitter authors’ messages. SVM is one of the commonly used and strong classification algorithms in authorship attribution problems. SVM maps the linearly non separable input data to a higher dimensional space by a hyperplane via radial base functions. Firstly using the training data, 10 hyperplanes that separate pair wise five authors training data are built. Then the expertise of these SVMs combined to classify the testing data into five classes. 20 tweets with 16 features from each author were used for evaluation. In spite of the randomly choice of the features, one of the author accuracy around 75% is achieved

Artificial Intelligence and Pattern Evidence: A Legal Application for AI

Artificial intelligence changes everything, and almost no jobs will be immune. The application of AI to the practice of law is well-known and well-understood. In this paper, we present some aspects of the related disciplines of forensic science and specifically the development and analysis of “pattern [and impression] evidence.” We show that pattern evidence has a great need for AI.We discuss several applications in detail but focus mostly on the application of AI-based text analysis technology to forensic linguistics.Sociedad Argentina de Informática e Investigación Operativ