Constructing social intentional corpora to predict click-through rate for search advertising

In the beginning, search engines provide placements next to the original search results for advertisers on specific keywords. Since users often search for their interests or purchasing decision, timely presenting proper advertisements to users will encourage them to click on search ads. With the rapid growth of advertising, there is a bidding mechanism that advertisers need to bid keywords on their ads. They should carefully compose keywords in order to enhance the opportunity for their ads to be clicked. 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.