Exploring the role of personality traits in followee recommendation

Abstract

Purpose

Followee recommendation is a problem rapidly gaining importance in Twitter as well as in other micro-blogging communities. To find interesting users to follow, most recommendation systems leverage different factors such as graph topology or user-generated content, among others. Those systems mostly disregard, however, the effect of psychological characteristics, such as personality, over the followee selection process. As personality is considered one of the primary factors that influence human behaviour, the purpose of this paper is to shed some light on the impact of personality traits on followee selection.

Design/methodology/approach

The authors performed a data analysis comparing the similarity among Twitter users and their followees regarding personality traits. The authors analysed three different similarity measures. First, the authors computed an overall similarity considering the five personality traits or dimensions of the Five-Factor model as a whole. Second, the authors computed the dimension-to-dimension similarity considering each individual personality trait independently of each other. Third, the authors computed a cross-dimension similarity considering each personality dimension in relation to the others.

Findings

This study showed that personality should be considered as a distinctive factor in the process of followee selection. However, personality dimensions should not be analysed as a whole as the overall personality similarity might not accurately assess the actual matching between individuals. Instead, the performed data analysis showed the existence of relations among the individual dimensions. Thus, the importance of considering each personality trait with respect to others is stated.

Originality/value

This study is among the firsts to study the impact of personality, one of the primary factors that influence human behaviour and social relationships, in the selection of followees in micro-blogging communities.

Publication
Online Information Review, Vol. 39 No. 6, pp. 812-830. https://doi.org/10.1108/OIR-04-2015-0107