Knowledge Commons of Institute of Automation,CAS
Mapping users across social media platforms by integrating text and structure information | |
Song Sun1,2; Qiudan Li1; Peng Yan1; Daniel Dajun Zeng1,2,3 | |
2017 | |
会议名称 | 2017 IEEE International Conference on Intelligence and Security Informatics, ISI 2017 |
页码 | 113-118 |
会议日期 | July 22-24, 2017 |
会议地点 | Beijing, China |
摘要 |
With the development of social media technology, users often register accounts, post messages and create friend links on several different platforms. Performing user identity mapping on multi-platform based on the behavior patterns of users is considerable for network supervision and personalization service. The existing methods focus on utilizing either text information or structure information alone. However, text information and structure information reflect different aspects of a user. An organic combination of them is beneficial to mining user behavior patterns, thus help identify users across platforms accurately. The challenging problems are the effective representation and similarity computation of the text and structure information. We propose a mapping method which integrates text and structure information. At first, the model represents user name, description, location information based on word2vec or string matching, and friend information represented as relation network is regarded as structure information. Then these information are used for similarity computation using Jaccard index or cosine similarity. After similarity computation, a linear model is adopted to get the overall similarity of user pairs to perform user mapping. Based on the proposed method, we develop a prototype system, which allows users to set and adjust the weights of different information, or set expected index. The experimental results on a real-world dataset demonstrate the efficiency of the proposed model. |
关键词 | User-mapping Cross-platform Similarity Computation Word2vec |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/15397 |
专题 | 多模态人工智能系统全国重点实验室_互联网大数据与信息安全 |
作者单位 | 1.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 China 2.University of Chinese Academy of Sciences, Beijing, China 3.Department of Management Information Systems, University of Arizona, Tucson, AZ 85721, USA |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Song Sun,Qiudan Li,Peng Yan,et al. Mapping users across social media platforms by integrating text and structure information[C],2017:113-118. |
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ISI2017.pdf(398KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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