You Want This Job? Influence and Interplay of Self-Generated Text and Picture Cues in Professional Networking Service Profiles on Expertise Evaluation

Abstract

ABSTRACT Job applicants’ self-presentation in their profiles on professional networking services (PNS), such as LinkedIn, may be crucial for the evaluation of their expertise for a job. Importantly, on PNS profiles, self-generated picture-based and text-based cues are shown together, and both may influence expertise evaluations. In three experiments, we systematically analyzed impression formation in the context of PNS profiles by investigating the influence of self-generated textual and pictorial cues on job applicants’ expertise evaluations. Student participants were presented with different PNS profiles that were systematically varied by the level of expertise (high vs. medium vs. low) conveyed through text (i.e., a description of experience and education) and pictures (i.e., a photo of the profile owner vs. a placeholder). Our results revealed a textual primacy in expertise evaluations of PNS profiles, as text expertise was crucial, independent of picture expertise. However, picture expertise was particularly important in cases of high text expertise. Placeholders always resulted in more negative judgments than high-expertise pictures and sometimes even had the same effect as low-expertise pictures. Finally, we discuss implications for theory building on impression formation and practical consequences for self-presentation in PNS.