Please use this identifier to cite or link to this item:
|Title:||CAVVA: Computational affective video-in-video advertising|
marketing and consumer psychology
|Citation:||Yadati, K., Katti, H., Kankanhalli, M. (2014-01). CAVVA: Computational affective video-in-video advertising. IEEE Transactions on Multimedia 16 (1) : 15-23. ScholarBank@NUS Repository. https://doi.org/10.1109/TMM.2013.2282128|
|Abstract:||Advertising is ubiquitous in the online community and more so in the ever-growing and popular online video delivery websites (e.g., YouTube). Video advertising is becoming increasingly popular on these websites. In addition to the existing pre-roll/post-roll advertising and contextual advertising, this paper proposes an in-stream video advertising strategy - Computational Affective Video-in-Video Advertising (CAVVA). Humans being emotional creatures are driven by emotions as well as rational thought. We believe that emotions play a major role in influencing the buying behavior of users and hence propose a video advertising strategy which takes into account the emotional impact of the videos as well as advertisements. Given a video and a set of advertisements, we identify candidate advertisement insertion points (step 1) and also identify the suitable advertisements (step 2) according to theories from marketing and consumer psychology. We formulate this two part problem as a single optimization function in a non-linear 0-1 integer programming framework and provide a genetic algorithm based solution. We evaluate CAVVA using a subjective user-study and eye-tracking experiment. Through these experiments, we demonstrate that CAVVA achieves a good balance between the following seemingly conflicting goals of (a) minimizing the user disturbance because of advertisement insertion while (b) enhancing the user engagement with the advertising content. We compare our method with existing advertising strategies and show that CAVVA can enhance the user's experience and also help increase the monetization potential of the advertising content. © 1999-2012 IEEE.|
|Source Title:||IEEE Transactions on Multimedia|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 14, 2018
WEB OF SCIENCETM
checked on Nov 28, 2018
checked on Dec 15, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.