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Modeling Islamist Extremist Communications on Social Media using Contextual Dimensions: Religion, Ideology, and Hate.

, , , , , , , , and . Proc. ACM Hum. Comput. Interact., 3 (CSCW): 151:1-151:22 (2019)

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Knowledge Infused Learning (K-IL): Towards Deep Incorporation of Knowledge in Deep Learning., , and . CoRR, (2019)Modeling Islamist Extremist Communications on Social Media using Contextual Dimensions: Religion, Ideology, and Hate., , , , , , , , and . Proc. ACM Hum. Comput. Interact., 3 (CSCW): 151:1-151:22 (2019)Defining and Detecting Toxicity on Social Media: Context and Knowledge are Key., , and . CoRR, (2021)Improving Contextual Congruence Across Modalities for Effective Multimodal Marketing using Knowledge-infused Learning., , , , and . CoRR, (2024)Cyber Social Threats 2020 Workshop Meta-report: COVID-19, Challenges, Methodological and Ethical Considerations., , , and . ICWSM Workshops, (2020)What's ur Type? Contextualized Classification of User Types in Marijuana-Related Communications Using Compositional Multiview Embedding., , , , , , , and . WI, page 474-479. IEEE Computer Society, (2018)Knowledge-infused Deep Learning., , , , and . HT, page 309-310. ACM, (2020)CySoc 2023: 4th International Workshop on Cyber Social Threats., , , , , and . WWW (Companion Volume), page 1307. ACM, (2023)Knowledge Infused Learning (K-IL): Towards Deep Incorporation of Knowledge in Deep Learning., , and . AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (1), volume 2600 of CEUR Workshop Proceedings, CEUR-WS.org, (2020)Social Media Analytics to Identify and Counter Islamist Extremism: Systematic Detection, Evaluation, and Challenging of Extremist Narratives Online., , and . CTS, page 611-612. IEEE Computer Society, (2016)