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Up or Down? Click-Through Rate Prediction from Social Intention for Search Advertising

Published: 02 December 2013 Publication History

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.

References

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cover image ACM Other conferences
IIWAS '13: Proceedings of International Conference on Information Integration and Web-based Applications & Services
December 2013
753 pages
ISBN:9781450321136
DOI:10.1145/2539150
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • @WAS: International Organization of Information Integration and Web-based Applications and Services

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 December 2013

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Author Tags

  1. Advertising
  2. Click-Through Rate
  3. Social Intention
  4. Sponsored Search

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