Abstract
The current study is based on the assumption that social topology and its interaction pattern affect users’ behavioral changes, especially continuity. To verify the hypothesis, several metrics have been introduced, and experiments have been conducted, resulting in interesting and quantitative findings. In the experiments, two conditional differences lead to statistic significance in continuity and other metrics; the first difference is the existence of feedback implementation, another one is information visibility. It has been experimentally confirmed that users who received more feedback from system bots (i.e., they did not know that they were controlled until the experiment ended) tend to also send more feedback themselves. Moreover, it has been found that only the fact that the others (i.e., bots), except the participant, sent feedback to each other made the person feel isolated, and the participant sent feedback him/herself to avoid being depressed with no interaction. On the other hand, information visibility had little effect on their continuity and no effect on their consciousness.
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Konishi, T., Nagata, M., Honjo, M., Yoneyama, A., Kurokawa, M., Mishima, K. (2019). Social Behaviors: A Social Topology and Interaction Pattern Affect the Properties of a Changed Behavior. In: Oinas-Kukkonen, H., Win, K., Karapanos, E., Karppinen, P., Kyza, E. (eds) Persuasive Technology: Development of Persuasive and Behavior Change Support Systems. PERSUASIVE 2019. Lecture Notes in Computer Science(), vol 11433. Springer, Cham. https://doi.org/10.1007/978-3-030-17287-9_25
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