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Up or down? Click-through rate prediction from social intention for search advertising
Conference paper

Up or down? Click-through rate prediction from social intention for search advertising

Yi-Ting Chen and Hung-Yu Kao
ACM International Conference Proceeding Series, pp.102-106
2013

Abstract

Advertising Click-Through Rate Social Intention Sponsored Search Software Human-Computer Interaction Computer Vision and Pattern Recognition Computer Networks and Communications
In search advertising, advertisers should carefully compose keywords in order to enhance the opportunity for ads to be clicked. Thus, timely presenting proper advertisements to users will encourage them to click on search ads. Until now, how to efficiently improve the ad performance to earn more clicks remains a main task. In this paper, we focus on the scope of smart phone and produce a social intentional model with advertising based features to forecast future trend on ads' click-through rate (CTR). In terms of social intentional model, we analyze Chinese text content of technology forum to derive social intentional factors which are Hotness, Sentiment, Promotion, and Event. Our results indicate that with knowing public opinions or occurring events beforehand can efficiently enhance click prediction. This will be very helpful for advertisers on adjusting bidding keywords to improve ad performance via social intention. © 2013 ACM.

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