Predicting online video engagement using clickstreams
| Autor: | Saurabh Nagrecha, Nitesh V. Chawla, Everaldo Aguiar |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
FOS: Computer and information sciences
I.5.2 Computer science business.industry Internet privacy Online video Space (commercial competition) Machine Learning (cs.LG) Computer Science - Information Retrieval World Wide Web Product (business) Computer Science - Learning User engagement Broadband Metric (mathematics) Position (finance) business Information Retrieval (cs.IR) Clickstream |
| Zdroj: | DSAA |
| DOI: | 10.1109/dsaa.2015.7344873 |
| Popis: | As access to broadband continues to grow along with the now almost ubiquitous availability of mobile phones, the landscape of the e-content delivery space has never been so dynamic. To establish their position in the market, businesses are beginning to realize that understanding each of their customers' likes and dislikes is perhaps as important as the offered content itself. Further, a number of companies are also delivering content, product previews, advertisements, etc. via video on their sites. The question remains — how effective are video engagement channels on sites? Can that user engagement be quantified? Clickstream data can furnish important insight into those questions using videos as a communication or messaging medium. To that end, focusing on a large set of web portals owned and managed by a private media company, we propose methods using these sites' clickstream data that can be used to provide a deeper understanding of their visitors, as well as their interests and preferences. We further expand the use of this data to show that it can be effectively used to predict user engagement to video streams, quantifying that metric by means of a survival analysis assessment. |
| Databáze: | OpenAIRE |
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