Exploiting User-Generated Content in Product Launch Videos to Compute a Launch Score

被引:0
|
作者
Das, Sibanjan Debeeprasad [1 ]
Bala, Pradip Kumar [1 ]
Das, Sukanta [2 ]
机构
[1] Indian Inst Management Ranchi, Ranchi 835303, India
[2] ICFAI Fdn Higher Educ, Fac Sci & Technol IcfaiTech, Dept Artificial Intelligence & Data Sci, Hyderabad 501203, Telangana, India
关键词
Text mining; social networks; emotions analysis; word-of-mouth; analytic models; marketing analytics; SOCIAL MEDIA ENGAGEMENT; CUSTOMER ENGAGEMENT; QUALITY ASSESSMENT; BEHAVIOR; CONSUMPTION; FRAMEWORK; FACEBOOK;
D O I
10.1109/ACCESS.2024.3381541
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This study investigated the relationship between the essential aspects of user-generated content (UGC) and product launch videos to derive the product launch score (PLS). This score can be considered a key performance indicator (KPI) to evaluate the performance of product launch videos. The product launch score can provide businesses and marketers with insights into how well the community and audience perceive a product launch on virtual social media platforms such as YouTube. The authors examined 52 product launch videos with a total of 1,11,716 comments on YouTube and analyzed the data to derive various sentimental, emotional, and social networking aspects from the comments on the product launch videos. Furthermore, the relationship between brand and product mentions was evaluated to determine the centrality of the launch activity. The work determined how effectively the community was engaged with the brand and product launch. Finally, relationship analysis and principal component analysis (PCA) were performed to select relevant aspects for calculating the PLS. This KPI provides a holistic view of user engagement in product launch videos.
引用
收藏
页码:49624 / 49639
页数:16
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