Detection of Branded Posts in User-Generated Content

被引：0
|
作者：
Levallois, Clement [1 ]
机构：
[1] Emlyon Business Sch, 15 Blvd Diderot, F-75012 Paris, France
来源：
SOCIAL COMPUTING AND SOCIAL MEDIA, PT II, SCSM 2024 | 2024年 / 14704卷
关键词：
user-generated content; branded content; text mining; Organic content; ONLINE; REVIEWS;
D O I：
10.1007/978-3-031-61305-0_21
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
User-generated content (UGC) is a fundamental source of information for the study of consumer behavior, product development, and to assess the quality of service. The expansion of branded content, published and mixed with "ordinary" UGC on the same online platforms, blurs the notions of which content should be considered for these studies. This contribution draws on the notion of "authenticity" to offer a taxonomy distinguishing "branded" from "organic" content and presents a computational method to detect branded content in UGC.
引用
收藏
页码：304 / 312
页数：9
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