Worth 1000 Words: The Effect of Social Cues on a Fundraising Campaign in a Government Agency. A

Housing is derived from the word house which means a place that has a place to live which will stay or stop in a certain time. Housing is a residence that has been grouped into a place that has facilities and infrastructure. The problem in this study focuses on the type of residential ownership in the form of SHM ART, SHM Non ART, NON SHM and others. These four types can be used to know the percentage of ownership in all provinces in Indonesia. Due to the fact that there is still a lot of information about the type of certificate ownership, there is still not much ownership. Therefore, the use of the k-Means algorithm as a data mining concept in the form of clusters, where the data already has parameters or values that fall into the category of unsupervised learning. That data produced the best. The data was obtained from published sources of the Republic of Indonesia government agency, namely the Central Statistics Agency data with the category of household processing with self-owned residential buildings purchased from developers or non-developers by province and type of ownership in 2016 throughout Indonesia. In conducting the dataset, researchers used the RapidMiner application as a clustering process application. This research shows that there are more types of ownership in the SHM ART, but for other values it is still smaller than the value in other types of ownership which is the second largest value. So, in this case, the role of government in providing assistance in the process of ownership in order to become SHM ART is very important.

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Does context matter? Effects of robot appearance and reliability on social attention differs based on lifelikeness of gaze task

10.31234/osf.io/aqk5s ◽

2020 ◽

Author(s):

Abdulaziz Abubshait ◽

Patrick P. Weis ◽

Eva Wiese

Keyword(s):

Cognitive Processing ◽

Social Cognitive ◽

Physical Appearance ◽

Mental States ◽

Social Attention ◽

Social Cues ◽

Social Signals ◽

Mind Perception ◽

The Social ◽

Behavioral Features

Social signals, such as changes in gaze direction, are essential cues to predict others’ mental states and behaviors (i.e., mentalizing). Studies show that humans can mentalize with non-human agents when they perceive a mind in them (i.e., mind perception). Robots that physically and/or behaviorally resemble humans likely trigger mind perception, which enhances the relevance of social cues and improves social-cognitive performance. The current ex-periments examine whether the effect of physical and behavioral influencers of mind perception on social-cognitive processing is modulated by the lifelikeness of a social interaction. Participants interacted with robots of varying degrees of physical (humanlike vs. robot-like) and behavioral (reliable vs. random) human-likeness while the lifelikeness of a social attention task was manipulated across five experiments. The first four experiments manipulated lifelikeness via the physical realism of the robot images (Study 1 and 2), the biological plausibility of the social signals (Study 3), and the plausibility of the social con-text (Study 4). They showed that humanlike behavior affected social attention whereas appearance affected mind perception ratings. However, when the lifelikeness of the interaction was increased by using videos of a human and a robot sending the social cues in a realistic environment (Study 5), social attention mechanisms were affected both by physical appearance and behavioral features, while mind perception ratings were mainly affected by physical appearance. This indicates that in order to understand the effect of physical and behavioral features on social cognition, paradigms should be used that adequately simulate the lifelikeness of social interactions.

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