소셜 미디어 빅데이터를 활용한 고향사랑기부제 분석

Purpose - This study analyzes how the Hometown Love Donation Program is discussed on online platforms using social media big data, aiming to identify its discourse structure and public perception. Design/methodology/approach - A total of 4,971 data points were collected from January 2023 to March 2025 across Naver, Daum, Google, and Facebook. Text mining, social network analysis (SNA), and CONCOR analysis were applied. Keyword characteristics and discourse structures were compared across channels. Findings - Keywords related to economic incentives—such as “Donation program,” “Donation,” “Incentive Gifts,” and “Tax Benefits”—were most prominent. Websites and news emphasized policy credibility; blogs and cafes highlighted personal experiences and benefits. Facebook focused on events and campaigns. Cluster analysis identified eight thematic clusters, including return gifts, tax benefits, and local engagement, confirming the program’s multi-layered nature. Research implications or Originality - This study provides a multi-channel analysis of public discourse on the Hometown Love Donation Program, addressing a research gap in this area. The findings offer foundational insights for developing channel-specific communication strategies. The prominence of return gifts and tax benefits as participation drivers highlights key considerations for future policy improvement.