[논문]유튜브의 개인화 알고리즘이 유도하는 적극이용 경로에 대한 실증분석

배승주

doi:10.9723/jksiis.2023.28.2.031

유튜브의 개인화 알고리즘이 유도하는 적극이용 경로에 대한 실증분석
An Empirical Analysis of the Active Use Paths induced by YouTube's Personalization Algorithm 원문보기

한국산업정보학회논문지 = Journal of the Korea Industrial Information Systems Research, v.28 no.2, 2023년, pp.31 - 45

배승주 (경성대학교 미디어콘텐츠학과)

초록
AI-Helper

본 연구는 유튜브 이용자의 사용 시간이 양적으로 증대하면서 나타나는 질적 단계와 경로에 주목하였다. 그리고 심리학과 신경과학의 이론을 적용하여 추천시스템의 개인화 알고리즘과 적극이용의 구간을 세분화하였고, 이론연구와 실증연구를 병행하였다. 이론연구에서 심리학과 신경과학의 관점으로 포그의 행동모델(FBM), 가변적 보상, 도파민 중독을 적용하였다. 포그의 행동모델(FBM)은 연관 콘텐츠 제시 기능인 개인화 추천 알고리즘이 트리거(계기)로서 쉬운 클릭을 유발하고, 가변적 보상은 검색하는 콘텐츠에 대한 예측불가능성으로 동기부여의 효과성을 높이며, 도파민 중독은 도파민 신경을 자극하면 지속적 적극적으로 콘텐츠를 소비하게 하는 것으로 요약된다. 본 연구는 개인화 추천 알고리즘과 적극이용 구간에서 콘텐츠의 이용 목적을 심리적 측면에서 처음이용, 재이용, 지속이용, 적극이용의 4단계로 구분하고, 경로를 분석하였다는 점에서 학문적 실무적 기여를 할 것으로 기대한다.

Abstract ▼ AI-Helper

This study deals with exploring qualitative steps and paths that appear as YouTube users' usage time increases quantitatively. For the study, I applied theories from psychology and neuroscience, subdivided the interval between the personalization algorithm of the recommendation system, and active use and analyzed the relationship between variables in this process. According to the theory behavioral model theory (FBM), variable reward, and dopamine addiction were applied. Personalization algorithms easy clicks as triggers according to associated content presentation functions in behavioral model theory (FBM). Variable rewards increase motivational effectiveness with unpredictability of the content you search, and dopamine nation is summarized as stimulating the dopaminergic nerve to continuously and actively consume content. This study is expected to make an academic and practical contribution in that it divides the purpose of use of content in the personalization algorithm and active use section into four stages from a psychological perspective: first use, reuse, continuous use, and active use, and analyzes the path.

주제어

표/그림 (4)

그림 Fig. 1 Research Model: Active Use Process by Recommendation Algorithm
표 Table 1 Results of Reliability and Validity Analysis
표 Table 2 AVE and SMC(Squared Multiple Correlations)
표 Table 3 Results of Model Estimated by AMOS

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표제어: PCR

동의어: Packet Collision Rate

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