Abstract
The appearance of massive open online courses has caused an increase in the volume of open online educational videos on the web. Therefore, there is a vast amount of information to be managed by the Internet users. The present work aims to optimize the educational video lecture searching in social networks. The research presents a novel ranking procedure for the educational video lectures that takes into account their popularity with content-based social media communities. The popularity formula combines quantitative and qualitative characteristics, taking into account not only the positive and the negative elements of the web page containing the video, but also the opinion of the users based on their comments. Thus, a novel social parameter is proposed which is embedded in the content-based ranking process. Furthermore, a user evaluation procedure is carried out, and initial results indicate that this integration produces a ranking output that better matches the user’s preferences.
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Kravvaris, D., Kermanidis, K.L. Advanced searching framework for open online educational video lectures. Soc. Netw. Anal. Min. 7, 31 (2017). https://doi.org/10.1007/s13278-017-0452-3
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DOI: https://doi.org/10.1007/s13278-017-0452-3