Name
Abstract | ||
|---|---|---|
With the rapid development of microblogs in recent years, accurate prediction of microblog user profiles is valuable for marketing, personalized recommendation, and legal investigation. Microblog users post rich contents everyday and build a complex friendship network with "following" behaviors. Both of user-generated content and friendship network are crucial for user profiling. In this work, we propose a neural-network based model for user profiling. It takes advantages of both user-generated content and friendship network with attentional multiscale convolutional neural networks and graph embeddings. We evaluate our model on SMP CUP 2016 dataset whose task is to infer age, gender and region of microblog users. The experiment results show that utilizing information from user generated content and friend network, our method obtains the state-of-the-art performance on all of three sub-tasks. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-981-10-6805-8_3 | Communications in Computer and Information Science |
Keywords | DocType | Volume |
Social network analysis,User profiling,Neural networks | Conference | 774 |
ISSN | ISBN | Citations |
1865-0929 | 9789811068041 | 0 |
PageRank | References | Authors |
0.34 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhao Zhishan | 1 | 0 | 0.34 |
| Du Jiachen | 2 | 36 | 9.02 |
| Gao Qinghong | 3 | 0 | 0.34 |
| Lin Gui | 4 | 94 | 12.82 |
| Xu Ruifeng | 5 | 432 | 53.04 |