Details
| Original language | English |
|---|---|
| Title of host publication | 1st International Workshop on Data Mining and Audience Intelligence for Advertising, ADKDD 2007, Held in Conjunction with SIGKDD'07 |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 46-54 |
| Number of pages | 9 |
| ISBN (print) | 9781595938336 |
| Publication status | Published - 12 Aug 2007 |
| Event | 1st International Workshop on Data Mining and Audience Intelligence for Advertising, ADKDD 2007, Held in Conjunction with SIGKDD'07 - San Jose, CA, United States Duration: 12 Aug 2007 → 12 Aug 2007 |
Publication series
| Name | 1st International Workshop on Data Mining and Audience Intelligence for Advertising, ADKDD 2007, Held in Conjunction with SIGKDD'07 |
|---|
Abstract
Allowing global distribution of information to large audiences at very low cost, the Internet has emerged as a vital medium for marketing and advertising. Weblogs, a new form of self publication on the Internet, have attracted online advertisers because of their incredible growth-rate in recent years. In this paper, we propose to discover information diffusion paths from the blogosphere to track how information frequently flows from blog to blog. This knowledge can be used in various applications of online campaign. Our approach is based on analyzing the content of blogs. After detecting trackable topics of blogs, we model a blog community as a blog sequence database. Then, the discovery of information diffusion paths is formalized as a problem of frequent pattern mining. We develop a new data mining algorithm to discover information diffusion paths. Experiments conducted on real life dataset show that our algorithm discovers information diffusion paths efficiently. The discovered information diffusion paths are accurate in predicting the future information flow in the blog community.
Keywords
- advertisement, blog mining, information diffusion
ASJC Scopus subject areas
- Computer Science(all)
- Artificial Intelligence
- Computer Science(all)
- Computer Graphics and Computer-Aided Design
- Computer Science(all)
- Software
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1st International Workshop on Data Mining and Audience Intelligence for Advertising, ADKDD 2007, Held in Conjunction with SIGKDD'07. Association for Computing Machinery (ACM), 2007. p. 46-54 (1st International Workshop on Data Mining and Audience Intelligence for Advertising, ADKDD 2007, Held in Conjunction with SIGKDD'07).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Discovering information diffusion paths from blogosphere for online advertising
AU - Stewart, Avaré
AU - Chen, Ling
AU - Paiu, Raluca
AU - Nejdl, Wolfgang
PY - 2007/8/12
Y1 - 2007/8/12
N2 - Allowing global distribution of information to large audiences at very low cost, the Internet has emerged as a vital medium for marketing and advertising. Weblogs, a new form of self publication on the Internet, have attracted online advertisers because of their incredible growth-rate in recent years. In this paper, we propose to discover information diffusion paths from the blogosphere to track how information frequently flows from blog to blog. This knowledge can be used in various applications of online campaign. Our approach is based on analyzing the content of blogs. After detecting trackable topics of blogs, we model a blog community as a blog sequence database. Then, the discovery of information diffusion paths is formalized as a problem of frequent pattern mining. We develop a new data mining algorithm to discover information diffusion paths. Experiments conducted on real life dataset show that our algorithm discovers information diffusion paths efficiently. The discovered information diffusion paths are accurate in predicting the future information flow in the blog community.
AB - Allowing global distribution of information to large audiences at very low cost, the Internet has emerged as a vital medium for marketing and advertising. Weblogs, a new form of self publication on the Internet, have attracted online advertisers because of their incredible growth-rate in recent years. In this paper, we propose to discover information diffusion paths from the blogosphere to track how information frequently flows from blog to blog. This knowledge can be used in various applications of online campaign. Our approach is based on analyzing the content of blogs. After detecting trackable topics of blogs, we model a blog community as a blog sequence database. Then, the discovery of information diffusion paths is formalized as a problem of frequent pattern mining. We develop a new data mining algorithm to discover information diffusion paths. Experiments conducted on real life dataset show that our algorithm discovers information diffusion paths efficiently. The discovered information diffusion paths are accurate in predicting the future information flow in the blog community.
KW - advertisement
KW - blog mining
KW - information diffusion
UR - http://www.scopus.com/inward/record.url?scp=77949552091&partnerID=8YFLogxK
U2 - 10.1145/1348599.1348607
DO - 10.1145/1348599.1348607
M3 - Conference contribution
AN - SCOPUS:77949552091
SN - 9781595938336
T3 - 1st International Workshop on Data Mining and Audience Intelligence for Advertising, ADKDD 2007, Held in Conjunction with SIGKDD'07
SP - 46
EP - 54
BT - 1st International Workshop on Data Mining and Audience Intelligence for Advertising, ADKDD 2007, Held in Conjunction with SIGKDD'07
PB - Association for Computing Machinery (ACM)
T2 - 1st International Workshop on Data Mining and Audience Intelligence for Advertising, ADKDD 2007, Held in Conjunction with SIGKDD'07
Y2 - 12 August 2007 through 12 August 2007
ER -