Automated conversational agents, also known as “chatbots” or “chatterbots,” are computer programs used in a variety of collaborative communications systems, often for entertainment or business purposes. However, their use as malicious tools has more recently made them a growing nuisance and security concern. We present a detailed graphical and statistical analysis of communication patterns (specifically involving message sizes and inter-message delays) for improving the detection of automated conversational agents in collaborative computer-mediated communication systems.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Graphical and statistical communication patterns of automated conversational agents in collaborative computer-mediated communication systems


    Beteiligte:
    McIntire, J (Autor:in) / Havig, P (Autor:in) / Farris, K (Autor:in) / McIntire, L (Autor:in)


    Erscheinungsdatum :

    01.07.2010


    Format / Umfang :

    870239 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Emotional Capabilities of Conversational Agents: A Review

    Jahn, Katharina / Rehren, Oliver / Schneider, Sascha et al. | DataCite | 2022


    AI-Driven Conversational Voice Communication for Maritime Autonomous Surface Ships

    Kim, Sanha / Ku, Jaebin / Lee, Eunkyu et al. | IEEE | 2025


    Computer Mediated Communication (CMC) and the Communication of Technical Information in Aerospace

    Kennedy, J. M. / Barclay, R. O. / Murphy, D. J. et al. | British Library Conference Proceedings | 1994


    Computer Mediated Communication (CMC) and the Communication of Technical Information in Aerospace

    Murphy, D. / AIAA | British Library Conference Proceedings | 1994


    COLLABORATIVE POSITIONING IN AUTOMATED CAR DRIVING: ACCOUNTING FOR COMMUNICATION CHANNEL AND MULTIPATH

    Mikhaylov, Nikolay / Schiegg, Florian A. / Li, Shuo et al. | British Library Conference Proceedings | 2020