TY - GEN
T1 - Probabilistic Models of Psychological Aspects in Computer-based Social Interactions
AU - Dolev, Shlomi
AU - Frenkel, Sergey
AU - Cwikel, Julie
AU - Zakharov, Victor
N1 - Publisher Copyright: © 2020 IEEE.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - The subject of the paper is the study of how to mathematically represent the phenomenon of the emergence of psychological and social situations in the process of interaction with various virtual objects, with an emphasis on the dangers that may arise in this interaction. These situations are considered in terms of emotions displayed by members of a social network, which, along with people interacting with computer interfaces, can also include avatars or bots.We argue that Markov chains, which are widely used for tasks of analyzing the optimization of social interaction (including such as interaction with humans and reactions of programs that support web navigation, interaction between humans and bots or between bots), do not reflect some aspects for which it is necessary to use such characteristics (concepts) as 'speed' and 'time'. More suitable are CTMC based models. A stochastic automaton network (SAN) is proposed as a high-level tool for representing the psychological interaction models described by CTMC.
AB - The subject of the paper is the study of how to mathematically represent the phenomenon of the emergence of psychological and social situations in the process of interaction with various virtual objects, with an emphasis on the dangers that may arise in this interaction. These situations are considered in terms of emotions displayed by members of a social network, which, along with people interacting with computer interfaces, can also include avatars or bots.We argue that Markov chains, which are widely used for tasks of analyzing the optimization of social interaction (including such as interaction with humans and reactions of programs that support web navigation, interaction between humans and bots or between bots), do not reflect some aspects for which it is necessary to use such characteristics (concepts) as 'speed' and 'time'. More suitable are CTMC based models. A stochastic automaton network (SAN) is proposed as a high-level tool for representing the psychological interaction models described by CTMC.
KW - Markov chains
KW - Social networks
KW - Stochastic automata networks
UR - https://www.scopus.com/pages/publications/85092006500
U2 - 10.1109/EnT48576.2020.00032
DO - 10.1109/EnT48576.2020.00032
M3 - Conference contribution
T3 - Proceedings - 2020 International Conference Engineering Technologies and Computer Science, EnT 2020
SP - 133
EP - 139
BT - Proceedings - 2020 International Conference Engineering Technologies and Computer Science, EnT 2020
A2 - Prokhorov, Sergei
T2 - 2020 International Conference Engineering Technologies and Computer Science, EnT 2020
Y2 - 24 June 2020 through 27 June 2020
ER -