Assessing the credibility of online social network messages.

ABSTRACT Information gathered socially online is a key feature of the growth and development of modern society. Presently the Internet is a platform for the distribution of data. Millions of people use Online Social Networks daily as a tool to get updated with social, political, educational or other occurrences. In many cases information derived from an Online Social Network is acted upon and often shared with other networks, without further assessments or judgments. Many people do not check to see if the information shared is credible. A user may trust the information generated by a close friend without questioning its credibility, in contrast to a message generated by an unknown user. This work considers the concept of credibility in the wider sense, by proposing whether a user can trust the service provider or even the information itself. Two key components of credibility have been explored; trustworthiness and expertise. Credibility has been researched in the past using Twitter as a validation tool. The research was focused on automatic methods of assessing the credibility of sets of tweets using analysis of microblog postings related to trending topics to determine the credibility of tweets. This research develops a framework that can assist the assessment of the credibility of messages in Online Social Networks. Four types of credibility are explored (experienced, surface, reputed and presumed credibility) resulting in a credibility hierarchy. To determine the credibility of messages generated and distributed in Online Social Networks, a virtual network is created, which attributes nodes with individual views to generate messages in the network at random, recording data from a network and analysing the data based on the behaviour exhibited by agents (an agent-based modelling approach). The factors considered for the experiment design included; peer-to-peer networking, collaboration, opinion formation and network rewiring. The behaviour of agents, frequency in which messages are shared and used, the pathway of the messages and how this affects credibility of messages is also considered. A framework is designed and the resulting data are tested using the design. The resulting data generated validated the framework in part, supporting an approach whereby the concept of tagging the message status assists the understanding and application of the credibility hierarchy. Validation was carried out with Twitter data acquired through twitter’s Application Programming Interface (API). There were similarities in the generation and frequency of the message distributions in the network; these findings were also recorded and analysed using the framework proposed. Some limitations were encountered while acquiring data from Twitter, however, there was sufficient evidence of correlation between the simulated and real social network datasets to indicate the validity of the framework.N/

Information Reliability on the Social Web - Models and Applications in Intelligent User Interfaces

The Social Web is undergoing continued evolution, changing the paradigm of information production, processing and sharing. Information sources have shifted from institutions to individual users, vastly increasing the amount of information available online. To overcome the information overload problem, modern filtering algorithms have enabled people to find relevant information in efficient ways. However, noisy, false and otherwise useless information remains a problem. We believe that the concept of information reliability needs to be considered along with information relevance to adapt filtering algorithms to today's Social Web. This approach helps to improve information search and discovery and can also improve user experience by communicating aspects of information reliability.This thesis first shows the results of a cross-disciplinary study into perceived reliability by reporting on a novel user experiment. This is followed by a discussion of modeling, validating, and communicating information reliability, including its various definitions across disciplines. A selection of important reliability attributes such as source credibility, competence, influence and timeliness are examined through different case studies. Results show that perceived reliability of information can vary greatly across contexts. Finally, recent studies on visual analytics, including algorithm explanations and interactive interfaces are discussed with respect to their impact on the perception of information reliability in a range of application domains