TY - GEN
T1 - Constructing social intentional corpora to predict click-through rate for search advertising
AU - Chen, Yi Ting
AU - Kao, Hung Yu
N1 - Publisher Copyright:
© ROCLING 2013.All rights reserved.
PY - 2013/10/1
Y1 - 2013/10/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84941980078&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84941980078&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84941980078
T3 - Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013
SP - 278
EP - 287
BT - Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013
PB - The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
T2 - 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013
Y2 - 4 October 2013 through 5 October 2013
ER -