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Contribution Details
| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | An information diffusion-based recommendation framework for micro-blogging |
| Organization Unit | |
| Authors |
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| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Journal Title | Journal of the Association for Information Systems |
| Publisher | Association for Information Systems |
| Geographical Reach | international |
| ISSN | 1536-9323 |
| Volume | 12 |
| Number | 7 |
| Page Range | 463 - 486 |
| Date | 2011 |
| Abstract Text | Micro-blogging is increasingly evolving from a daily chatting tool into a critical platform for individuals and organizations to seek and share real-time news updates during emergencies. However, seeking and extracting useful information from micro-blogging sites poses significant challenges due to the volume of the traffic and the presence of a large body of irrelevant personal messages and spam. In this paper, we propose a novel recommendation framework to overcome this problem. By analyzing information diffusion patterns among a large set of micro-blogs that play the role of emergency news providers, our approach selects a small subset as recommended emergency news feeds for regular users. We evaluate our diffusion-based recommendation framework on Twitter during the early outbreak of H1N1 Flu. The evaluation results show that our method results in more balanced and comprehensive recommendations compared to benchmark approaches. |
| Official URL | http://aisel.aisnet.org/jais/vol12/iss7/2/ |
| Other Identification Number | merlin-id:6373 |
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