Trail of Journey: An Analysis of Digital Footprints on Content Attributes and Initiation of Filipino Travel-Related Contents on Youtube

• Published in: 2022 2nd International Conference in Information and Computing Research (iCORE) pp. 264 - 269
• Main Authors: Socuaji, Aila Mae B., Note, Kimberly Ashley R., Remetio, Ella Grace G., Tolete, Rica Jane V., Vallan, Critchimae Allen, Lapuz, Mark Chris M.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-12-2022
• Subjects: Content Attributes; Content Initiation; Correlation; Digital Footprint; Linear regression; Social networking (online); Strategic planning; Systematics; Tourism industry; Video on demand
• DOI: 10.1109/iCORE58172.2022.00064

As the world revolves around social media, where anything is easily accessible because every click leaves traces on the internet, this study provided the importance of digital footprint focused on its engagements. Utilizing the YouTube platform, this research studied the underlying correlation of three (3) constructs which are Digital Footprint, Content Attributes, and Content Initiation, with the leading research problem that focused on the predictive relationship of the variables through a widely used video engine. The researchers performed a predictive correlation technique utilizing a quantitative approach. Towards the sampling design, researchers used a purposive sampling technique to select valid content creators. The latter will be observed for their digital footprint and the information of their travel-related content. The researchers used a set of criteria and systematic data screening to address the study's objective. With the aid of netnography and inter-rater, this study has been thoroughly checked and validated by experts and professionals. This research answered the predictive relationship of the three variables, and the results indicated that Destination Featured, Duration of the Video, and Sponsored or Self-Initiated types of travel-related content were all significant to Digital Footprints. Hence, the Types of Tourist Attractions were insignificant. The data were analyzed using multiple linear regression, which showed the significance and correlation of each variable.