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| Author(s): |
Luís Fernando Dorelli de Abreu
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | São Carlos. |
| Institution: | Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) |
| Defense date: | 2016-08-03 |
| Examining board members: |
Francisco Aparecido Rodrigues;
Paulino Ribeiro Villas Boas;
Angélica Sousa da Mata;
Gonzalo Travieso
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| Advisor: | Francisco Aparecido Rodrigues |
| Abstract | |
The raise in the availability of data regarding interactions between people online has opened new doors to study the process of information diffusion in social networks. In this present work, we make use of the data from the micro-blogging website Twitteralong with complex networks concepts to understand, characterize and classify information diffusion processes observed in this platform and in social networks in general. We present important measures to characterize information cascades and efficient algorithms to calculate them. With the help of these measures, we show that it is possible to quantify the influence of the social network in the process of information diffusion. After that, we show that information does tend to travel along shortest paths on Twitter. Finally, we show that the topology of the social network, without any extra semantic information, can be used to aggregate topics, and that such topology is highly influenced by the topics being discussed on it. Altough we work with only a single dataset, our methods and measures developed are general and can be applied to any process of information diffusion and any complex network. (AU) | |
| FAPESP's process: | 14/12335-0 - Structure and dynamics of information networks |
| Grantee: | Luís Fernando Dorelli de Abreu |
| Support Opportunities: | Scholarships in Brazil - Master |