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    政大機構典藏 > 理學院 > 資訊科學系 > 期刊論文 >  Item 140.119/110579
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/110579


    Title: Exploiting Concept Drift to Predict Popularity of Social Multimedia in Microblogs
    Authors: 沈錳坤
    Li, Cheng-Te;Shan, Man-Kwan;Jheng, Shih-Hong;Chou, Kuan-Ching
    Contributors: 資科系
    Keywords: Popularity prediction;Social multimedia;Concept drift;Information diffusion;Microblog social network
    Date: 2016-04
    Issue Date: 2017-06-29 09:43:08 (UTC+8)
    Abstract: Microblogging services such as Twitter and Plurk allow users to easily access and share different types of social multimedia (e.g. images and videos) in the cyber world. However, the massive amount of information available causes information overload, which prevents users from quickly accessing popular and important digital content. This paper studies the problem of predicting the popularity of social multimedia content embedded in short microblog messages. A property of social multimedia is that it can be continuously re-shared, thus its popularity may revive or evolve over time. We exploit the idea of concept drift to capture this property. We formulate the problem using a classification-based approach and propose to tackle two tasks, re-share classification and popularity score classification. Two categories of features are devised and extracted, including information diffusion and explicit multimedia meta information. We develop a concept drift-based popularity predictor by ensembling multiple trained classifiers from social multimedia instances in different time intervals. The key idea lies in dynamically determining the ensemble weights of classifiers. Experiments conducted on Plurk and Twitter datasets show the high accuracy of the popularity classification and the results on detecting popular social multimedia are promising.
    Relation: Information Sciences, 339, 310-331
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1016/j.ins.2016.01.009
    DOI: 10.1016/j.ins.2016.01.009
    Appears in Collections:[資訊科學系] 期刊論文

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