Detecting predatory behavior in game chats

The WEKA data mining software: an update

Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., & Witten, I. H. (2009) · ACM SIGKDD Explorations Newsletter · doi:10.1145/1656274.1656278 · Cited by 17,750 · see citing works

The Development and Psychometric Properties of LIWC2015

Pennebaker, J. W., Boyd, R. L., Jordan, K., & Blackburn, K. (2015) · University of Texas at Austin · doi:10.15781/t25p41 · Cited by 1,674 · see citing works

Data Mining for Imbalanced Datasets: An Overview

Chawla, N. V. (2009) · Springer eBooks · doi:10.1007/978-0-387-09823-4_45 · Cited by 1,092 · see citing works

A new ANEW: Evaluation of a word list for sentiment analysis in microblogsPreprint

Nielsen, F. Å. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1103.2903 · Cited by 733 · see citing works

Risks and safety on the internet: the perspective of European children: full findings and policy implications from the EU Kids Online survey of 9-16 year olds and their parents in 25 countries

Livingstone, S., Haddon, L., Görzig, A., & Ólafsson, K. (2011) · London School of Economics and Political Science Research Online (London School of Economics and Political Science) · Cited by 631 · see citing works

Data Mining for Imbalanced Datasets: An Overview

Chawla, N. V. (2006) · Springer eBooks · doi:10.1007/0-387-25465-x_40 · Cited by 449 · see citing works

Predicting age and gender in online social networks

Peersman, C., Daelemans, W., & Van Vaerenbergh, L. (2011) · Proceedings of the 3rd international workshop on Search and mining user-generated contents · doi:10.1145/2065023.2065035 · Cited by 260 · see citing works

Entrapping the innocent: Toward a theory of child sexual predators’ luring communication

Olson, L. N., Daggs, J. L., Ellevold, B. L., & Rogers, T. K. K. (2007) · Communication Theory · doi:10.1111/j.1468-2885.2007.00294.x · Cited by 160 · see citing works

Learning to Identify Internet Sexual Predation

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Overview of the International Sexual Predator Identification Competition at PAN-2012.

Inches, G., & Crestani, F. (2012) · Cited by 93 · see citing works

Toward spotting the pedophile telling victim from predator in text chats

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Reliability of human annotation of semantic roles in noisy text

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Text Mining and Cybercrime

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A Two-step Approach for Effective Detection of Misbehaving Users in Chats

Villatoro-Tello, E., Juárez-González, A., Escalante, H. J., Montes-y-Gómez, M., & Villaseñor-Pineda, L. (2012) · Cited by 41 · see citing works

Untitled work

(2012) · Cited by 28 · see citing works

A Learning-Based Approach for the Identification of Sexual Predators in Chat Logs.

Parapar, J., Losada, D. E., & Barreiro, Á. (2012) · CLEF (Online Working Notes/Labs/Workshop) · Cited by 27 · see citing works

Conversation Level Constraints on Pedophile Detection in Chat Rooms

Peersman, C., Vaassen, F., Asch, V. V., & Daelemans, W. M. P. (2012) · Bristol Research (University of Bristol) · Cited by 23 · see citing works

Identifying Sexual Predators by SVM Classification with Lexical and Behavioral Features.

Morris, C. W., & Hirst, G. (2012) · Cited by 23 · see citing works

Identifying Predators Using ChatCoder 2.0.

Kontostathis, A., Garron, A., Reynolds, K., West, W. H., & Edwards, L. (2012) · CLEF (Online Working Notes/Labs/Workshop) · Cited by 14 · see citing works

Combining Predation Heuristics and Chat-Like Features in Sexual Predator Identification.

Hidalgo, J. M. G., & Díaz, A. A. C. (2012) · CLEF (Online Working Notes/Labs/Workshop) · Cited by 14 · see citing works

Features for Modelling Characteristics of Conversations.

Eriksson, G., & Jussi Karlgren, C. (2012) · CLEF (Online Working Notes/Labs/Workshop) · Cited by 10 · see citing works

Elements of traditional and “reverse” purism in relation to computer-mediated communication

Hohenhaus, P. (2005) · De Gruyter eBooks · doi:10.1515/9783110901351.204 · Cited by 6 · see citing works

World Wide Web and the Formation of the Chinese and English "Internet Slang Union"

Yan, Y. (2006) · Computer-assisted Foreign Language Education · Cited by 3 · see citing works

Detecting Predatory Behaviour in Online Game Chats

Gudnadottir, E. R., Jensen, A. K., Cheong, Y.-G., Togelius, J., Bae, B.-C., & Pedersen, C. H. (2013) · IT University Of Copenhagen (IT University of Copenhagen) · Cited by 1 · see citing works

A Human-Centered Systematic Literature Review of the Computational Approaches for Online Sexual Risk Detection

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Cyber-aggression, Cyberbullying, and Cyber-grooming: A Survey and Research Challenges

Mladenović, M., Ošmjanski, V., & Stanković, S. V. (2022) · ACM Computing Surveys · doi:10.1145/3424246 · Cited by 79 · see citing works

Early detection of deception and aggressiveness using profile-based representations

Escalante, H. J., Villatoro-Tello, E., Garza, S. E., López-Monroy, A. P., Montes-y-Gómez, M., & Villaseñor-Pineda, L. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2017.07.040 · Cited by 44 · see citing works

A Technology Acceptance Model-Based Analytics for Online Mobile Games Using Machine Learning Techniques

Chauhan, S., Mittal, M., Woźniak, M., Gupta, S., & de Prado, R. P. (2021) · Symmetry · doi:10.3390/sym13081545 · Cited by 47 · see citing works

Online grooming detection: A comprehensive survey of child exploitation in chat logs

Borj, P. R., Raja, K., & Bours, P. (2023) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.110039 · Cited by 38 · see citing works

Child Safety and Protection in the Online Gaming Ecosystem

Faraz, A., Mounsef, J., Raza, A., & Willis, S. (2022) · IEEE Access · doi:10.1109/access.2022.3218415 · Cited by 40 · see citing works

Mitigating Online Sexual Grooming Cybercrime on Social Media Using Machine Learning: A Desktop Survey

Ngejane, C. H., Mabuza-Hocquet, G., Eloff, J. H. P., & Lefophane, S. (2018) · International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD) · doi:10.1109/icabcd.2018.8465413 · Cited by 33 · see citing works

Sexual Violence in Virtual Reality: A Scoping Review

Porta, C. M., Frerich, E. A., Hoffman, S., Bauer, S., Jain, V. M., & Bradley, C. (2024) · Journal of Forensic Nursing · doi:10.1097/jfn.0000000000000466 · Cited by 17 · see citing works

Early Detection of Sexual Predators in Chats

Vogt, M., Leser, U., & Akbik, A. (2021) · doi:10.18653/v1/2021.acl-long.386 · Cited by 18 · see citing works

The Language of Online Child Sexual Groomers - A Corpus Assisted Discourse Study of Intentions, Requests and Grooming Duration

Kinzel, A. (2021) · doi:10.23889/suthesis.59027 · Cited by 17 · see citing works

Exposing patterns of adult solicitor behaviour: towards a theory of control within the cybersexual abuse of youth

Barber, C. S., & Bettez, S. C. (2021) · European Journal of Information Systems · doi:10.1080/0960085x.2020.1816146 · Cited by 12 · see citing works

How to take advantage of behavioral features for the early detection of grooming in online conversations

Milon-Flores, D. F. (2022) · doi:10.11606/d.55.2022.tde-01082022-150335 · Cited by 12 · see citing works

Antecedents of Cloud Gaming Acceptance among Gen Z: Achieving Sustainability in the Digital Gaming Industry

Gumasing, M. J., Alonzo, R. F. B., Nazareno, J., & Guinto, K. L. D. (2023) · Sustainability · doi:10.3390/su15129189 · Cited by 9 · see citing works

Effectiveness of machine learning methods in detecting grooming: a systematic meta-analytic review

Bianchi, M. L., Castillo, N., Astudillo, C. A., & Ahumada-Méndez, F. (2025) · Scientific Reports · doi:10.1038/s41598-024-83003-4 · Cited by 13 · see citing works

Deploying Human-Centered Machine Learning to Improve Adolescent Online Sexual Risk Detection Algorithms

Razi, A. (2019) · International ACM SIGGROUP Conference on Supporting Group Work (GROUP) · doi:10.1145/3323994.3372138 · Cited by 8 · see citing works

On preprocessing the data for improving sexual predator detection: Anonymous for review

Borj, P. R., Raja, K., & Bours, P. (2020) · 2020 15th International Workshop on Semantic and Social Media Adaptation and Personalization (SMA · doi:10.1109/smap49528.2020.9248461 · Cited by 8 · see citing works

Analysis of Online Conversations to Detect Cyberpredators Using Recurrent Neural Networks.

Kim, J.-H., Kim, Y. J., Behzadi, M., & Harris, I. G. (2020) · Cited by 6 · see citing works

The Age of Analytics

Bauckhage, C., Drachen, A., & Thurau, C. (2015) · IEEE Transactions on Computational Intelligence and AI in Games · doi:10.1109/tciaig.2015.2467166 · Cited by 5 · see citing works

Comparing machine learning models with a focus on tone in grooming chat logs

Hamm, L., & McKeever, S. (2025) · Frontiers in Pediatrics · doi:10.3389/fped.2025.1591828 · Cited by 4 · see citing works

Osprey 🪶: A Reference Framework for Online Grooming Detection via Neural Models and Conversation Features

Waezi, H., Barzegar, R., & Fani, H. (2024) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3627673.3679974 · Cited by 2 · see citing works

Enhanced Online Grooming detection employing Context Determination and Message-Level Analysis

Street, J., Ihianle, I. K., Olajide, F., & Lotfi, A. (2025) · Intelligent Systems with Applications · doi:10.1016/j.iswa.2025.200607 · Cited by 6 · see citing works

Identificação de predadores sexuais brasileiros em conversas textuais na internet por meio de aprendizagem de máquina

dos Santos, L. F., & Guedes, G. P. (2020) · iSys - Brazilian Journal of Information Systems · doi:10.5753/isys.2020.822 · Cited by 1 · see citing works

“FRIENDLY CHAT”- A chat application with multi-headed classification models for identifying abusive levels and their comparative study

Parkavi, A., Sowmya, B. J., & Pushpalatha, M. N. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1706/1/012145 · Cited by 1 · see citing works

It's All in the Game - an Exploration of Extensive Communication on Gaming Platforms and the Risks of Online Sexual GroomingPreprint

Drejer, C., Sabet, S. S., Baugerud, G. A., & Riegler, M. A. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4671140 · Cited by 1 · see citing works

Utilizando Teoria da Informação para Identificar Conversas de Pedofilia em Redes Sociais de Mensagens Instantâneas

Postal, J. G., & Nakamura, E. F. (2017) · Simpósio Brasileiro de Sistemas Colaborativos (SBSC) · doi:10.5753/sbsc.2017.9957

Strategies to use Prior Knowledge to Improve the Performance of Deep Learning (Subtitle) An Approach Towards Trustable Machine Learning Systems

Morgan, J. (2022) · doi:10.23889/suthesis.59258

The Missing Resources for Child Online Risk Detection

Prosser, E., Peersman, C., & Edwards, M. (2026) · ACM Computing Surveys · doi:10.1145/3806384

Player Safety by Design: Co-Designing Child-Centered Safety Mechanisms with Children

Zhang, Z., Song, Q., Hernandez, R. H., Liu, Y., Koung, E., Yu, J., Bai, S., Kou, Y., & Gui, X. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791090

Building Target-Language Cybergrooming Detectors from English-Language Datasets: A Machine Translation Pipeline

Jaeckel, L., Stickler, Q., & Labudde, D. (2026) · Information · doi:10.3390/info17090831

Trust, Enjoyment, and the Conditional Acceptance of Cloud Gaming Among Engaged Generation Z Gamers in Brazil: A PLS-SEM Analysis With Moderation and Predictive Assessment

Mariano, A. M., Borges, I. R., Santos, M. R., Constatin, A. C. C., & Tavares, F. G. M. (2026) · IEEE Access · doi:10.1109/access.2026.3729987

Detecting Predatory Behaviour in Game Chats

Cheong, Y.-G., Jensen, A. K., Gudnadottir, E. R., Bae, B.-C., & Togelius, J. (2015)

Protectbot: A Chatbot to Protect Children on Gaming Platforms

Faraz, A. (2022) · RIT Scholar Works (Rochester Institute of Technology)

Detecting Sexually Predatory Behavior on Open-Access Online Forums

Singla, Y. (2021) · Advances in intelligent systems and computing · doi:10.1007/978-981-16-1543-6_3 · Cited by 1 · see citing works

Detecting Predatory Behaviour from Online Textual Chats

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Combining psycho-linguistic, content-based and chat-based features to detect predation in chatrooms

Barreiro, A., Losada, D. E., & Parapar, J. (2014) · Verlag der Technischen Universität Graz · doi:10.3217/jucs-020-02-0213 · Cited by 16 · see citing works