With the growing use of popular social media services like Facebook and Twitter it is hard to collect all content from the networks without access to the core infrastructure or paying for it. Thus, ...
@cite_2 discuss different methods to transverse social networks from a crawling perspective by focusing on public groups rather than individual users' profiles. Our approach mainly differs from this study in two ways. First, we do not create a social network to transverse and only treat the social media as data, i.e., our proposed method does not require any knowledge of the underlying network. Secondly, we focus on user interactions represented as so called Social Interaction Network (SIN) graphs @cite_0 as it shows the interactions between users in various communities, i.e., SIN graphs can represent interactions of all users on one particular newsgroup or users interacting on a specific topic. To conclude, there are no prior studies, according to our literature review, that address the challenge of collecting data from Facebook after Facebook changed the default privacy policy of its end-users' content. Most studies use online data repositories and do not address the issue of how to efficiently collect data directly from Facebook, or other social media sites.
@cite_0 @cite_2
2068140991 1986435040
Online Social Networks (OSNs) are popular platforms for interaction, communication and collaboration between friends. In this paper we develop and present a new platform to make interactions in OSNs accessible. Most of today's social networks, including Facebook, Twitter, and Google+ provide support for third party applications to use their social network graph and content. Such applications are strongly dependent on the set of software tools and libraries provided by the OSNs for their own development and growth. For example, third party companies like CNN provide recommendation materials based on user interactions and user's relationship graph. One of the limitations with this graph (or APIs) is the segregation from the shared content. We believe, and present in this paper, that the content shared and the actions taken on the content, creates a Social Interaction Network (SIN). As such, we extend Facebook's current API in order to allow applications to retrieve a weighted graph instead of Facebooks unweighted graph. Finally, we evaluate the proposed platform based on completeness and speed of the crawled results from selected community pages. We also give a few example uses of our API on how it can be used by third party applications. In new generation social networks, we expect that the paradigm of Social Internetworking Systems (SISs) will become progressively more important. Indeed, the possibility of interconnecting users and resources of different social networks enables a lot of strategic applications whose main strength is the integration of different communities that nevertheless preserves their diversity and autonomy. In this new scenario, the role of Social Network Analysis is crucial in studying the evolution of structures, individuals, interactions, and so on, and in extracting powerful knowledge from them. But the preliminary step to do is designing a good way to crawl the underlying graph. Although this aspect has been deeply investigated in the field of social networks, it is an open issue when moving towards SISs. Indeed, we cannot expect that a crawling strategy, specifically designed for social networks, is still valid in a Social Internetworking Scenario, due to its specific topological features. In this paper, we confirm the above claim, giving a strong motivation for our second contribution, which is the definition of a new crawling strategy. This strategy, specifically conceived for SISs, is shown to fully overcome the drawbacks of the state-of-the-art crawling strategies.