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Affinity-driven blog cascade analysis and prediction

หน่วยงาน Nanyang Technological University, Singapore

รายละเอียด

ชื่อเรื่อง : Affinity-driven blog cascade analysis and prediction
นักวิจัย : Li, Hui , Bhowmick, Sourav S. , Sun, Aixin , Cui, Jiangtao
คำค้น : DRNTU::Engineering::Computer science and engineering.
หน่วยงาน : Nanyang Technological University, Singapore
ผู้ร่วมงาน : -
ปีพิมพ์ : 2556
อ้างอิง : Li, H., Bhowmick, S. S., Sun, A., & Cui, J. (2013). Affinity-driven blog cascade analysis and prediction. Data mining and knowledge discovery. , http://hdl.handle.net/10220/17314 , http://dx.doi.org/10.1007/s10618-013-0307-0
ที่มา : -
ความเชี่ยวชาญ : -
ความสัมพันธ์ : Data mining and knowledge discovery
ขอบเขตของเนื้อหา : -
บทคัดย่อ/คำอธิบาย :

Information propagation within the blogosphere is of much importance in implementing policies, marketing research, launching new products, and other applications. In this paper, we take a microscopic view of the information propagation pattern in blogosphere by investigating blog cascade affinity. A blog cascade is a group of posts linked together discussing about the same topic, and cascade affinity refers to the phenomenon of a blog’s inclination to join a specific cascade. We identify and analyze an array of macroscopic and microscopic content-oblivious features that may affect a blogger’s cascade joining behavior and utilize these features to predict cascade affinity of blogs. Based on these features, we present two non-probabilistic and probabilistic strategies, namely support vector machine (SVM) classification-based approach and Bipartite Markov Random Field-based (BiMRF) approach, respectively, to predict the probability of blogs’ affinity to a cascade and rank them accordingly. Evaluated on a real dataset consisting of 873,496 posts, our experimental results demonstrate that our prediction strategy can generate high quality results ( F1 -measure of 72.5 % for SVM and 71.1 % for BiMRF) comparing with the approaches using traditional or singular features only such as elapsed time, number of participants which is around 11.2 and 8.9 %, respectively. Our experiments also showed that among all features identified, the number of quasi-friends is the most important factor affecting bloggers’ inclination to join cascades.

บรรณานุกรม :
Li, Hui , Bhowmick, Sourav S. , Sun, Aixin , Cui, Jiangtao . (2556). Affinity-driven blog cascade analysis and prediction.
    กรุงเทพมหานคร : Nanyang Technological University, Singapore.
Li, Hui , Bhowmick, Sourav S. , Sun, Aixin , Cui, Jiangtao . 2556. "Affinity-driven blog cascade analysis and prediction".
    กรุงเทพมหานคร : Nanyang Technological University, Singapore.
Li, Hui , Bhowmick, Sourav S. , Sun, Aixin , Cui, Jiangtao . "Affinity-driven blog cascade analysis and prediction."
    กรุงเทพมหานคร : Nanyang Technological University, Singapore, 2556. Print.
Li, Hui , Bhowmick, Sourav S. , Sun, Aixin , Cui, Jiangtao . Affinity-driven blog cascade analysis and prediction. กรุงเทพมหานคร : Nanyang Technological University, Singapore; 2556.