Affiliation:
1. Kansas State University, USA
Abstract
Network Overview, Discovery and Exploration for Excel (NodeXL Basic) enables the extraction of “user” (entity), “video” (content), and pseudo multi-modal networks from YouTube. This open-source add-on to NodeXL captures a wide range of data, enables data processing for analysis, and then visualization in a variety of graphs (based on different layout algorithms). This chapter summarizes some of the “askable” questions using this approach. Various types of data extractions are shared to give a sense of the breadth of some approaches, including the following: (1) entities, (2) in-world phenomena, (3) imaginary phenomena, (4) themes, (5) reputations by name, (6) genres, (7) language-specific phenomena, and (8) location-specific phenomena.
Reference42 articles.
1. Abisheva, A., Garimella, V. R. K., Garcia, D., & Weber, I. (2014). Who watches (and shares) what on YouTube? And when? Using Twitter to understand YouTube viewership. In Proceedings of WSDM ’14.
2. Baluja, S., Seth, R., Sivakumar, D., Jing, Y., Yagnik, J., Kumar, S., . . . Aly, M. (2008). Video suggestion and discovery for YouTube: Taking random walks through the view graph. In Proceedings of WWW 2008: Industrial Practice and Experience.
3. Understanding video interactions in youtube
4. Social network sites: Definition, history, and scholarship.;D. M.Boyd;Journal of Computer-Mediated Communication,2008