Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/114645
Title: Attribution errors and biases in assigning personality traits to actors based on roles they interpret
Authors: Mifsud, Andre (2022)
Keywords: Actors -- Malta
Personality -- Malta
Issue Date: 2022
Citation: Mifsud, A. (2022). Attribution errors and biases in assigning personality traits to actors based on roles they interpret (Higher Diploma long essay).
Abstract: TV actors tend to be perceived by viewers as having the same characteristics of their fictional characters. Some studies interpret this is as viewers’ fundamental attribution error in ignoring the script as a situational determiner of fictional characters’ behaviour and instead attributing it to TV actors’ own personality (Tal-Or & Papirman, 2007; Tukachinsky, 2020). This study investigates how TV actors experience these misattributions through semistructured interviews conducted with six Maltese actors using Reflexive Thematic Analysis (Braun & Clarke, 2006, 2021a, 2021b). Actors in this study talk about blurred boundaries in actor-character distinction, not just for viewers but even for the participants themselves. Viewers ascribe characters’ traits and experiences to actors, who they often see as blended with characters. Participants describe these misattributions as independent of time and context and dependent on popularity of TV shows, geographical location of viewers, and if characters are negative. Professional and emotional implications for actors are also discussed, with participants noting both positive and negative repercussions. Although experiences were mixed, participants overall feel content with their careers and report these misattributions increase their role satisfaction. Notably, however, due to the study’s small sample size, results cannot be generalised.
Description: H.Dip.(Melit.)
URI: https://www.um.edu.mt/library/oar/handle/123456789/114645
Appears in Collections:Dissertations - FacSoW - 2022
Dissertations - FacSoWPsy - 2022

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