Instagram推薦機制對年輕用戶社交行為與同溫層效應之影響

Abstract

隨著社群媒體的快速崛起，越來越多人透過這些平台進行日常互動和企業推廣。Instagram作為一個以視覺內容為核心、深受年輕族群喜愛的平台，因其高度依賴推薦機制而備受關注。本研究以Instagram為對象，檢視Instagram用戶是否因平台推薦機制而影響社交行為，同時探討同溫層效應於平台互動中的展現。本研究採用量化問卷調查法，以18至34歲具Instagram使用經驗者為對象，共回收有效樣本333份。問卷設計包含四大構面：「互動意願」、「社交拓展」、「興趣強化」與「同溫層效應」，並透過單一與多元迴歸分析進行資料處理與假設驗證。研究結果顯示，Instagram推薦機制能有效促進用戶的互動意願與社交拓展，並強化其原有的興趣偏好。進一步分析指出，這些互動行為亦能顯著預測同溫層效應的程度，特別是當用戶的內容興趣越集中時，與使用者的互動參與度也跟著提升。此外，性別與年齡對於推薦機制所影響的社交行為並無顯著差異，顯示平台演算機制已趨向以使用行為為主的個人化推薦模式。

With the rapid rise of social media, more and more people are using these platforms for daily interactions and business promotion. Instagram, a visual-centric platform particularly popular among young people, has attracted much attention due to its heavy reliance on recommendation algorithms. This study focuses on Instagram and examines whether its recommendation mechanism influences users’ social behaviors, while also exploring how the echo chamber effect manifests in platform interactions. A quantitative questionnaire survey was conducted among users aged 18 to 34 with Instagram experience, yielding a total of 333 valid responses. The questionnaire consisted of four key dimensions: “Interaction Intention,” “Social Expansion,” “Interest Reinforcement,” and “Echo Chamber Effect.” Data were analyzed using simple and multiple regression analyses to test the proposed hypotheses. The findings show that Instagram’s recommendation mechanism effectively enhances users’ interaction intention and social expansion, while also strengthening their existing interest preferences. Further analysis revealed that these interactive behaviors significantly predict the level of the echo chamber effect, especially as users’ content interests become more focused, leading to greater interaction participation. Additionally, no significant differences were found in social behaviors influenced by the recommendation mechanism across gender and age groups, indicating that the platform’s algorithm increasingly favors behavior-based personalized recommendations.