Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 15th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2013 |
| Pages | 102-106 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 2013 Dec 1 |
| Event | 15th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2013 - Vienna, Austria Duration: 2013 Dec 2 → 2013 Dec 4 |
Publication series
| Name | ACM International Conference Proceeding Series |
|---|
Other
| Other | 15th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2013 |
|---|---|
| Country | Austria |
| City | Vienna |
| Period | 13-12-02 → 13-12-04 |
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All Science Journal Classification (ASJC) codes
- Human-Computer Interaction
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Software
Cite this
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Up or down? Click-through rate prediction from social intention for search advertising. / Chen, Yi Ting; Kao, Hung-Yu.
Proceedings - 15th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2013. 2013. p. 102-106 (ACM International Conference Proceeding Series).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Up or down? Click-through rate prediction from social intention for search advertising
AU - Chen, Yi Ting
AU - Kao, Hung-Yu
PY - 2013/12/1
Y1 - 2013/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84896816824&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84896816824&partnerID=8YFLogxK
U2 - 10.1145/2539150.2539249
DO - 10.1145/2539150.2539249
M3 - Conference contribution
AN - SCOPUS:84896816824
SN - 9781450321136
T3 - ACM International Conference Proceeding Series
SP - 102
EP - 106
BT - Proceedings - 15th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2013
ER -