What determines levels of interpersonal attraction? A long history of research in social psychology has highlighted a range of important factors, such as physical attractiveness, similarity of attitudes and beliefs, reciprocity of feelings, self-disclosure of personal information, and familiarity. One theme that runs through several of these characteristics is the concept of uncertainty, and in particular how reducing uncertainty in knowledge about a person influences levels of attraction. According to the Uncertainty Reduction Theory (URT), as an individual’s uncertainty in a person diminishes, levels of attraction are expected to rise. Previous research, however, has reported a mixed and somewhat complicated relationship between uncertainty and attraction, possibly moderated by the current stage of the interpersonal relationship. 

 

One limitation of this area of enquiry is that the methods used to reduce uncertainty have tended to focus on the amount of available information rather than its quality. This shortcoming has become increasingly salient with the rise of online social networking, where people have a wide range of strategies available to reduce uncertainty through passive (non-interactive) observation, for instance by studying profile details or other online information about a person. In the current study, Kuge et al. (2024) aim to partially fill this gap by examining the role of uncertainty reduction by altering the abstractness (or specificity) of available information, rather than its quantity, particularly in an observational, non-interactive setting. According to the tenets of URT, the authors predict firstly that participants will rate a person described in more concrete terms as more attractive than one described using abstract terms, and secondly that perceived uncertainty will mediate the effect of the abstractness on levels of attraction.

 

To test these hypotheses, the authors begin with an online survey (N=250) to select pairs of sentences with varying levels of abstractness while ensuring they are matched for favourability. Then in the main study (N=1000) they will test the effect of the selected abstract vs. concrete expressions on levels of attractiveness, in addition to control variables such as how confident the participant is in predicting the person’s behaviour, as well as a manipulation check to confirm the effectiveness of the abstractness manipulation. Confirmation of these hypotheses would add support for URT, while disconfirmation may indicate that the theory is inadequate at explaining the drivers of attraction in online unilateral communication.

 

 

Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA.
 
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Kuge, H., Otsubo, K., Hattori, K., Urakawa, M., & Yamada. Y (2024). Attraction depending on the level of abstraction of the character descriptions. In principle acceptance of Version 4 by Peer Community in Registered Reports. https://osf.io/28f4q