New Automation for Social Bots: From Trivial Behavior to AI-Powered Communication

Attention Is All You Need

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017) · arXiv · doi:10.48550/arxiv.1706.03762 · Cited by 120,404 · see citing works

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) · doi:10.18653/v1/n19-1423 · Cited by 48,293 · see citing works

Human-level control through deep reinforcement learning

Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., Graves, A., Riedmiller, M., Fidjeland, A. K., Ostrovski, G., et al. (2015) · Nature · doi:10.1038/nature14236 · Cited by 30,357 · see citing works

Language Models are Few-Shot Learners

Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020) · arXiv · doi:10.48550/arxiv.2005.14165 · Cited by 23,372 · see citing works

BLEU: a method for automatic evaluation of machine translation

Papineni, K., Roukos, S., Ward, T., & Zhu, W.-J. (2001) · Proceedings of the 40th Annual Meeting on Association for Computational Linguistics - ACL '02 · doi:10.3115/1073083.1073135 · Cited by 21,344 · see citing works

Mastering the game of Go with deep neural networks and tree search

Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., van den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al. (2016) · Nature · doi:10.1038/nature16961 · Cited by 15,612 · see citing works

Computer-Mediated Communication: Impersonal, Interpersonal, and Hyperpersonal Interaction

WALTHER, J. B. (1996) · Communication Research · doi:10.1177/009365096023001001 · Cited by 4,798 · see citing works

The Uncanny Valley [From the Field]

Mori, M., MacDorman, K., & Kageki, N. (2012) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2012.2192811 · Cited by 3,542 · see citing works

Hierarchical Text-Conditional Image Generation with CLIP Latents

Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., & Chen, M. (2022) · arXiv · doi:10.48550/arxiv.2204.06125 · Cited by 2,511 · see citing works

The rise of social bots

Ferrara, E., Varol, O., Davis, C., Menczer, F., & Flammini, A. (2016) · Communications of the ACM · doi:10.1145/2818717 · Cited by 1,973 · see citing works

All One Needs to Know about Metaverse: A Complete Survey on Technological Singularity, Virtual Ecosystem, and Research Agenda

Lee, L., Braud, T., Zhou, P., Wang, L., Xu, D., Lin, Z., Kumar, A., Bermejo, C., & Hui, P. (2024) · Foundations and Trends® in Human–Computer Interaction · doi:10.1561/1100000095 · Cited by 1,525 · see citing works

Fundamentals of modern manufacturing : materials, processes, and systems

Groover, M. P. (1996) · Cited by 1,358 · see citing works

All One Needs to Know about Metaverse: A Complete Survey on Technological Singularity, Virtual Ecosystem, and Research Agenda

Lee, L.-H., Braud, T., Zhou, P., Wang, L., Xu, D., Lin, Z., Kumar, A., Bermejo, C., & Hui, P. (2021) · arXiv · doi:10.48550/arxiv.2110.05352 · Cited by 1,088 · see citing works

Social bots distort the 2016 U.S. Presidential election online discussion

Bessi, A., & Ferrara, E. (2016) · First Monday · doi:10.5210/fm.v21i11.7090 · Cited by 993 · see citing works

What is XR? Towards a Framework for Augmented and Virtual Reality

Rauschnabel, P. A., Felix, R., Hinsch, C., Shahab, H., & Alt, F. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107289 · Cited by 931 · see citing works

Custodians of the Internet: Platforms, Content Moderation, and the Hidden Decisions That Shape Social Media

Gillespie, T. (2019) · doi:10.12987/9780300235029 · Cited by 806 · see citing works

In the shades of the uncanny valley: An experimental study of human–chatbot interaction

Ciechanowski, L., Przegalińska, A., Magnuski, M., & Gloor, P. A. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.01.055 · Cited by 680 · see citing works

Psychological, Relational, and Emotional Effects of Self-Disclosure After Conversations With a Chatbot

Ho, A., Hancock, J., & Miner, A. S. (2018) · Journal of Communication · doi:10.1093/joc/jqy026 · Cited by 629 · see citing works

Computers are social actors

Nass, C., Steuer, J., & Tauber, E. R. (1994) · Conference companion on Human factors in computing systems - CHI '94 · doi:10.1145/259963.260288 · Cited by 579 · see citing works

Almost human? A comparative case study on the social media presence of virtual influencers

Arsenyan, J., & Mirowska, A. (2021) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2021.102694 · Cited by 566 · see citing works

Experience-Driven Procedural Content Generation

Yannakakis, G. N., & Togelius, J. (2011) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2011.6 · Cited by 536 · see citing works

The thing that should not be: predictive coding and the uncanny valley in perceiving human and humanoid robot actions

Saygin, A. P., Chaminade, T., Ishiguro, H., Driver, J., & Frith, C. (2012) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsr025 · Cited by 452 · see citing works

The Paradigm-Shift of Social Spambots: Evidence, Theories, and Tools for the Arms Race

Cresci, S., Di Pietro, R., Petrocchi, M., Spognardi, A., & Tesconi, M. (2017) · Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion · doi:10.1145/3041021.3055135 · Cited by 381 · see citing works

Untitled work

(2020) · doi:10.1609/aaai.v34i01.5460 · Cited by 361 · see citing works

Empirical evaluation and new design for fighting evolving Twitter spammers

Yang, C., Harkreader, R., & Gu, G. (2013) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2013.2267732 · Cited by 346 · see citing works

A decade of social bot detection

Cresci, S. (2020) · Communications of the ACM · doi:10.1145/3409116 · Cited by 323 · see citing works

Is that a bot running the social media feed? Testing the differences in perceptions of communication quality for a human agent and a bot agent on Twitter

Edwards, C. C., Edwards, A. P., Spence, P. R., & Shelton, A. K. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.08.013 · Cited by 315 · see citing works

Metaverse: Security and Privacy Issues

Pietro, R. D., & Cresci, S. (2021) · IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA) · doi:10.1109/tpsisa52974.2021.00032 · Cited by 295 · see citing works

Automatic Detection of Generated Text is Easiest when Humans are Fooled

Ippolito, D., Duckworth, D., Callison-Burch, C., & Eck, D. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2020.acl-main.164 · Cited by 264 · see citing works

Automatic Detection of Generated Text is Easiest when Humans are Fooled

Ippolito, D., Duckworth, D., Callison-Burch, C., & Eck, D. (2019) · arXiv · doi:10.48550/arxiv.1911.00650 · Cited by 264

TweepFake: about detecting deepfake tweets

Fagni, T., Falchi, F., Gambini, M., Martella, A., & Tesconi, M. (2021) · PLOS ONE · doi:10.1371/journal.pone.0251415 · Cited by 185 · see citing works

The False positive problem of automatic bot detection in social science research

Rauchfleisch, A., & Kaiser, J. (2020) · PLOS ONE · doi:10.1371/journal.pone.0241045 · Cited by 184 · see citing works

Evaluating the Effectiveness of Deplatforming as a Moderation Strategy on Twitter

Jhaver, S., Boylston, C., Yang, D., & Bruckman, A. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3479525 · Cited by 169 · see citing works

Social Bots: Human-Like by Means of Human Control?

Grimme, C., Preuß, M., Adam, L., & Trautmann, H. (2017) · Big Data · doi:10.1089/big.2017.0044 · Cited by 165 · see citing works

Help! Is my chatbot falling into the uncanny valley? An empirical study of user experience in human-chatbot interaction

Skjuve, M. B., Haugstveit, I. M., Følstad, A., & Brandtzæg, P. B. (2019) · Human Technology · doi:10.17011/ht/urn.201902201607 · Cited by 143 · see citing works

Generating Sentiment-Preserving Fake Online Reviews Using Neural Language Models and Their Human- and Machine-Based Detection

Adelani, D. I., Mai, H., Fang, F., Nguyen, H. H., Yamagishi, J., & Echizen, I. (2020) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-44041-1_114 · Cited by 108 · see citing works

Turing's test and believable AI in games

Livingstone, D. (2006) · Computers in entertainment · doi:10.1145/1111293.1111303 · Cited by 104 · see citing works

Demystifying Social Bots: On the Intelligence of Automated Social Media Actors

Assenmacher, D., Clever, L., Frischlich, L., Quandt, T., Trautmann, H., & Grimme, C. (2020) · Social Media + Society · doi:10.1177/2056305120939264 · Cited by 100 · see citing works

Coordinated Behavior on Social Media in 2019 UK General Election

Nizzoli, L., Tardelli, S., Avvenuti, M., Cresci, S., & Tesconi, M. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v15i1.18074 · Cited by 95 · see citing works

Changing Perspectives: Is It Sufficient to Detect Social Bots?

Grimme, C., Assenmacher, D., & Adam, L. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-91521-0_32 · Cited by 93 · see citing works

Procedural Content Generation: Goals, Challenges and Actionable Steps

Togelius, J., Champandard, A. J., Lanzi, P. L., Mateas, M., Paiva, A., Preuß, M., & Stanley, K. O. (2013) · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · doi:10.4230/dfu.vol6.12191.61 · Cited by 91 · see citing works

A Survey on Multimodal Disinformation DetectionPreprint

Alam, F., Cresci, S., Chakraborty, T., Silvestri, F., Dimitrov, D., Martino, G. D. S., Shaar, S., Firooz, H., & Nakov, P. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.12541 · Cited by 77 · see citing works

From Chess and Atari to StarCraft and Beyond: How Game AI is Driving the World of AI

Risi, S., & Preuss, M. (2020) · Künstliche Intell. · doi:10.1007/s13218-020-00647-w · Cited by 72 · see citing works

Amplifying influence through coordinated behaviour in social networks

Weber, D., & Neumann, F. (2021) · Social Network Analysis and Mining · doi:10.1007/s13278-021-00815-2 · Cited by 72 · see citing works

Orchestrating Game Generation

Liapis, A., Yannakakis, G. N., Nelson, M. J., Preuß, M., & Rafael Bidarra, E. (2018) · IEEE Transactions on Games · doi:10.1109/tg.2018.2870876 · Cited by 72 · see citing works

The Metaverse, or the Serious Business of Tech Frontiers

Knox, J. (2022) · Postdigital Science and Education · doi:10.1007/s42438-022-00300-9 · Cited by 67 · see citing works

A Generalist Agent

Reed, S., Zolna, K., Parisotto, E., Colmenarejo, S. G., Novikov, A., Barth-Maron, G., Gimenez, M., Sulsky, Y., Kay, J., Springenberg, J. T., et al. (2022) · arXiv · doi:10.48550/arxiv.2205.06175 · Cited by 63 · see citing works

LOBO: Evaluation of Generalization Deficiencies in Twitter Bot Classifiers

Echeverra, J., De Cristofaro, E., Kourtellis, N., Leontiadis, I., Stringhini, G., & Zhou, S. (2018) · Proceedings of the 34th Annual Computer Security Applications Conference · doi:10.1145/3274694.3274738 · Cited by 61 · see citing works

Make Reddit Great Again: Assessing Community Effects of Moderation Interventions on r/The_Donald

Trujillo, A., & Cresci, S. (2022) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3555639 · Cited by 57 · see citing works

Differences in perceptions of communication quality between a Twitterbot and human agent for information seeking and learning

Edwards, C. C., Beattie, A. J., Edwards, A. P., & Spence, P. R. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.07.003 · Cited by 56 · see citing works

New Dimensions of Information Warfare

Pietro, R. D., Raponi, S., Caprolu, M., & Cresci, S. (2020) · Advances in information security · doi:10.1007/978-3-030-60618-3 · Cited by 53 · see citing works

Explicating Cues: A Typology for Understanding Emerging Media Technologies

Xu, K., & Liao, T. (2019) · Journal of Computer-Mediated Communication · doi:10.1093/jcmc/zmz023 · Cited by 50 · see citing works

MAGMA – Multimodal Augmentation of Generative Models through Adapter-based Finetuning

Eichenberg, C., Black, S., Weinbach, S., Parcalabescu, L., & Frank, A. (2022) · Findings of the Association for Computational Linguistics: EMNLP 2022 · doi:10.18653/v1/2022.findings-emnlp.179 · Cited by 49 · see citing works

Synthesized Social Signals: Computationally-Derived Social Signals from Account Histories

Im, J., Tandon, S., Chandrasekharan, E., Denby, T., & Gilbert, É. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376383 · Cited by 39 · see citing works

Bots in Social and Interaction Networks

Mendoza, M., Tesconi, M., & Cresci, S. (2020) · ACM Transactions on Information Systems · doi:10.1145/3419369 · Cited by 36 · see citing works

Artificial intelligence against hate: Intervention reducing verbal aggression in the social network environment

Bilewicz, M., Tempska, P., Leliwa, G., Dowgiałło, M., Tańska, M., Urbaniak, R., & Wroczyński, M. (2021) · Aggressive Behavior · doi:10.1002/ab.21948 · Cited by 30 · see citing works

Uncanny Valley Effects on Friendship Decisions in Virtual Social Networking Service

Shin, M., Song, S. W., & Chock, T. M. (2019) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2019.0122 · Cited by 29 · see citing works

Characterizing Social Bots Spreading Financial Disinformation

Tardelli, S., Avvenuti, M., Tesconi, M., & Cresci, S. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-49570-1_26 · Cited by 29 · see citing works

How Relevant Is the Turing Test in the Age of Sophisbots?

Boneh, D., Grotto, A., McDaniel, P. D., & Papernot, N. (2019) · IEEE Security & Privacy · doi:10.1109/msec.2019.2934193 · Cited by 28 · see citing works

‘The bot predicted rain, grab an umbrella’: few perceived differences in communication quality of a weather Twitterbot versus professional and amateur meteorologists

Spence, P. R., Edwards, A. P., Edwards, C. C., & Jin, X. (2018) · Behaviour and Information Technology · doi:10.1080/0144929x.2018.1514425 · Cited by 27 · see citing works

Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem

Assenmacher, D., Weber, D., Preuß, M., Valdez, A. S. C., Bradshaw, A., Roß, B., Cresci, S., Trautmann, H., Neumann, F., & Grimme, C. (2021) · Social Science Computer Review · doi:10.1177/08944393211012268 · Cited by 27 · see citing works

Personalized Interventions for Online Moderation

Cresci, S., Trujillo, A., & Fagni, T. (2022) · ACM Conference on Hypertext and Social Media (HT) · doi:10.1145/3511095.3536369 · Cited by 25 · see citing works

PETGEN

He, B., Ahamad, M., & Kumar, S. (2021) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3447548.3467390 · Cited by 19 · see citing works

Reading Social Media Marketing Messages as Simulated Self Within a Metaverse: An Analysis of Gaze and Social Media Engagement Behaviors within a Metaverse Platform

Jeon, Y. A. (2022) · IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) · doi:10.1109/vrw55335.2022.00068 · Cited by 18 · see citing works

Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Study

Tekiroğlu, S. S., Bonaldi, H., Fanton, M., & Guerini, M. (2022) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2022.findings-acl.245 · Cited by 18 · see citing works

The coming age of adversarial social bot detection

Cresci, S., Petrocchi, M., Spognardi, A., & Tognazzi, S. (2021) · First Monday · doi:10.5210/fm.v26i7.11474 · Cited by 13 · see citing works

Automatic Story Generation: Challenges and AttemptsPreprint

Alabdulkarim, A., Li, S., & Peng, X. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2102.12634 · Cited by 7 · see citing works

“She Seems More Human”: Understanding Twitter Users’ Credibility Assessments of Dementia-Related Information

Alhayan, F., Pennington, D. R., & Ruthven, I. G. (2022) · Lecture notes in computer science · doi:10.1007/978-3-030-96960-8_20 · Cited by 2 · see citing works

Guest Editorial Special Issue on Team AI in Games

Mozgovoy, M., Preuß, M., & Rafael Bidarra, E. (2021) · IEEE Transactions on Games · doi:10.1109/tg.2021.3127967 · Cited by 2 · see citing works

Anatomy of an AI-powered malicious social botnet

Yang, K., & Menczer, F. (2024) · Journal of Quantitative Description: Digital Media · doi:10.51685/jqd.2024.icwsm.7 · Cited by 71 · see citing works

Semi-Supervised Social Bot Detection with Relational Graph Attention Transformers and Characteristics of the social environment

Huang, D., Song, J., & Zhang, X. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.102956 · Cited by 14 · see citing works

Dispelling the Fake: Social Bot Detection Based on Edge Confidence Evaluation

Qiao, B., Zhou, W. J., Li, K., Li, S., & Hu, S. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3396192 · Cited by 12 · see citing works

Demystifying Misconceptions in Social Bots Research

Cresci, S., Yang, K.-C., Spognardi, A., Pietro, R. D., Menczer, F., & Petrocchi, M. (2025) · Social Science Computer Review · doi:10.1177/08944393251376707 · Cited by 12 · see citing works

Lost in Transformation: Rediscovering LLM-Generated Campaigns in Social Media

Britta, G., Pohl, J., Winkelmann, H., Stampe, L., & Grimme, C. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-47896-3_6 · Cited by 9 · see citing works

BotSSCL: Social Bot Detection with Self-Supervised Contrastive Learning

Akhtar, M. M., Bhuiyan, N. S., Masood, R., Ikram, M., & Kanhere, S. S. (2025) · Online Social Networks and Media · doi:10.1016/j.osnem.2025.100318 · Cited by 8 · see citing works

Navigating Ambiguities: A Systematic Review and Comparative Analysis of Social Bot Detection Methods in Communication Research

Meng, X., Wang, X.-H., & Peng, T.-Q. (2026) · Communication Methods and Measures · doi:10.1080/19312458.2026.2613829 · Cited by 5 · see citing works

Temporal Neighbor Sequence-based Interpretable Spammer Groups Detection on E-commerce platform

Li, N., Ji, S., Dou, Y., Chiu, D. K. W., Zhang, Q., Liang, Y., & Wei, Y. (2025) · Information Processing & Management · doi:10.1016/j.ipm.2025.104177 · Cited by 6 · see citing works

Benchmarking Sentence Embeddings in Textual Stream Clustering with Applications to Campaign Detection

Stampe, L., Pohl, J., Britta, G., & Grimme, C. (2024) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn60899.2024.10650595 · Cited by 2 · see citing works

Early Malware Characterization based on Online Social Networks

Sadighian, A., Abbes, I., & Oligeri, G. (2023) · International Conference on Advanced Communication Technologies and Networking (CommNet) · doi:10.1109/commnet60167.2023.10365252 · Cited by 1 · see citing works

Contesting Control with Automation in Technology-Mediated Interactions

Boudouraki, A., Cameron, H., Reyes-Cruz, G., Avila, J. P. M., Orduna, M., Castro, S. V., & Kohonen-Aho, L. (2025) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3706599.3719855

Algorithmic Branding

Totz, C. (2025) · Springer eBooks · doi:10.1007/978-3-658-46355-7_2

Unmasking Influence: The Power of Artificial Entities in Shaping Public Opinion on Social Networks

Rabiee, H., Ladani, B. T., & Sahafizadeh, E. (2025) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2025.3631707

Perception Toward AI in Culture: Current Trends and Future Challenges

Moura, F. T. (2026) · Springer eBooks · doi:10.1007/978-3-031-75316-9_57-1

Out of Order: On the Importance of Word Positions in Explaining Text Classification

Stockdiek, J. L., Britta, G., Griesbach, M., & Grimme, C. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-21477-5_29

BotCHF: camouflage-heterogeneity-aware fusion for social bot detection

Wang, X., Shi, S., Qiao, K., Hu, H., Liu, Z., Zhang, Y., Han, J., & Yan, B. (2026) · Journal of King Saud University - Computer and Information Sciences · doi:10.1007/s44443-026-01013-w

Beyond Brokerage: The Connectivity Enhancement Mechanism of Artificial Intelligence Power in Homogeneous Networks

Tao, S., Zhao, Y., & Hong, T. (2026) · Systems · doi:10.3390/systems14070817

Piloting the Integration of AI-Driven Detection Methods to Counter Disinformation in Organizational Processes

Stampe, L., & Grimme, C. (2026) · Media and Communication · doi:10.17645/mac.12460

Socialbots at the Gates. Plädoyer für eine holistische Perspektive auf automatisierte Akteure in der Umwelt des Journalismus

Muhle, F. (2022) · Medien & Kommunikationswissenschaft · doi:10.5771/1615-634x-2022-1-2-40 · Cited by 7 · see citing works

Demystifying Misconceptions in Social Bots Research

Cresci, S., Yang, K.-C., Spognardi, A., Pietro, R. D., Menczer, F., & Petrocchi, M. (2025) · Social Science Computer Review · doi:10.1177/08944393251376707 · Cited by 12 · see citing works

Measuring Human–Bot Interactions

Varol, O. (2020) · The International Encyclopedia of Media Psychology · doi:10.1002/9781119011071.iemp0299

Balancing Act: Automated GenAI Outputs and Their Impact on Social Media Ecosystems

Patel, H. (2025) · ACM SIGCAS Computers and Society · doi:10.1145/3749886.3749889 · Cited by 1 · see citing works

Archaeology of Social Robots: The Evolution of Manipulated Interactions in the Age of AI under X

Brachotte, G. (2026) · EPISTÉMÈ · doi:10.38119/cacs.2026.37.8