Tweet reach : a research protocol for using Twitter to increase information exchange in people with communication disabilities

Objective: To (a) outline the background to research evaluating Twitter use by people with severe physical and communication disabilities participating actively in online communication forums for increasing information exchange and (b) illustrate a range of potential methods that might be applied in furthering research on the use of social media by people with developmental and acquired communication disabilities. Methods: The literature on communication disabilities, augmentative and alternative communication, and social media research informed the rationale for and design of three studies investigating the use of Twitter by people with communication disabilities. Results: To date, there is little information in the literature about how people with a range of communication disabilities might use Twitter to increase their access to information and help them to feel knowledgeable and in control of their own lives. In this paper, three studies are proposed to investigate the use of Twitter by people with communication disabilities.

Mining mechanism of top-k influential nodes based on voting algorithm in mobile social networks

In recent years, evaluating the influence of nodes and finding top-k influential nodes in social networks, has drawn a wide attention and has become a hot-pot research issue. Considering the characteristics of social networks, we present a novel mechanism to mine the top-k influential nodes in mobile social networks. The proposed mechanism is based on the behaviors analysis of SMS/MMS (simple messaging service / multimedia messaging service) communication between mobile users. We introduce the complex network theory to build a social relation graph, which is used to reveal the relationship among people's social contacts and messages sending. Moreover, intimacy degree is also introduced to characterize social frequency among nodes. Election mechanism is hired to find the most influential node, and then a heap sorting algorithm is used to sort the voting results to find the k most influential nodes. The experimental results show that the mechanism can finds out the most influential top-k nodes efficiently and effectively. © 2013 IEEE.