Titlebook: Internet Science; 5th International Co Svetlana S. Bodrunova Conference proceedings 2018 Springer Nature Switzerland AG 2018 artificial int

的事物

Neural Network Hate Deletion: Developing a Machine Learning Model to Eliminate Hate from Online Comm and find that our method reduces hatefulness without resulting in a significant loss of understandability. In some cases, removing hateful elements improves understandability by reducing the linguistic complexity of the comment. In addition, we find that NNHD can satisfactorily retain the original

nocturnal

Adaptive Focused Crawling Using Online Learningls: (i) ., where a user manually evaluates the discovered resources, and (ii) ., where the framework uses the already trained classifiers to assess the relevance of newly discovered resources. The evaluation experiments in the domain of Islamic extremism indicate the effectiveness of online learning

NEX

Using Corpus Linguistics Tools to Analyze a Russian-Language Islamic Extremist Forumtify most frequent words and word clusters, build concordances, find collocates, etc. A comparative corpus analysis of texts by Islamic extremists and those by common Internet users on the same topic (comments on relevant newsfeeds) allowed us to identify a number of features of Islamic extremist rh

虛度

Image of International Migration in Russian Online Mass Media problems. In addition to the analysis of the broadcasted content on migration, we also studied the opinion of Russians on that content and its presentation in media. As a result, a number of trends have been revealed in presentation of international migration processes by electronic mass media and

micturition

欺騙手段

follicular-unit

悠然

What Makes Users Trust a Chatbot for Customer Service? An Exploratory Interview Studyeived security and privacy in the chatbot, as well as general risk perceptions concerning the topic of the request. Implications for the design and development of chatbots and directions for future work are suggested.

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