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- W3000687342 abstract "In this paper, we present a rule based method to classify Tweets under three main categories; terrorism, violence and threat classes. Given that Arabic is a morphologically complex language, we build a linguistic module to identify a set of patterns for each class. Our proposed method requires three fundamental steps: First, we create our reference corpus collected from Arabic tweets. From the study of this corpus, we identify a set of linguistic rules. Finally, these patterns will be rewritten into local grammar within the linguistic platform NooJ. The evaluation of our system achieved encouraging results to obtaining 84%, 86.8% and 84.7% in terms of recall, precision and f-score respectively, when applied to test corpus." @default.
- W3000687342 created "2020-01-23" @default.
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- W3000687342 date "2020-01-01" @default.
- W3000687342 modified "2023-09-24" @default.
- W3000687342 title "Rule Based Method for Terrorism, Violence and Threat Classification: Application to Arabic Tweets" @default.
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- W3000687342 doi "https://doi.org/10.1007/978-3-030-38833-1_18" @default.
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