ABSTRACT
Trust in social network is a vital aspect when it comes to interaction between users in social network. When we go online, there are a lot of people connected to each other, numerous number of posts, videos and photos uploaded. What are the benchmark that we put to trust someone or an information on social network? Especially when that person has no connection with us in real life. Basically, we tend to look at their user’s profile, with whom they are friend, how many followers did they have and also numbers of like, share and comment on their post before we approve them on our friend list or trust the post on timeline. In this project, we use a pragmatic approach which is by applying Trust theory by Surya Nepal in a research paper entitle "An association based approach to Propagate Trust in Social Networks" that considers two aspect of trust which is Popularity Trust (PopTrust) and Engagement Trust (EngTrust). Our goal is to extract relevant information about node presenting “friend” and exploit Facepager and Gephi simulator to discover the relation of these node and prove the trusted data in the social network.
INTRODUCTION
Trust is something that is difficult to establish. In contrast, in social network context, it is almost possible for someone to trust another person within less than an hour. For instance, an actress who has high popularity in a social network based on engagement with other social media users basically would have higher trust in their network circumstance compared to a person who just create a social media account and have no interaction or engagement with any other social media users.
There is a saying “In order to establish trust, it is first important that you be trustworthy. This means you should be forthright with all your dealings.” If you’re a trustworthy person, you’re not going to tarnished your reputation in social network. This lead to a motivation for me to conduct a project on analysing trusted data in social network by applying Trust theory integrating with Facepager and Gephi simulator.
Trust is a major concern when using information from social networks. This research proposes to consider trust in the social media information used. We propose to use an approach to trust which takes into account a variety of aspects including location of sender, past behaviour, and reputation in other social networks. Our goal is to achieved the trust via relation and interaction between nodes in graph.
There is a saying “In order to establish trust, it is first important that you be trustworthy. This means you should be forthright with all your dealings.” If you’re a trustworthy person, you’re not going to tarnished your reputation in social network. This lead to a motivation for me to conduct a project on analysing trusted data in social network by applying Trust theory integrating with Facepager and Gephi simulator.
Trust is a major concern when using information from social networks. This research proposes to consider trust in the social media information used. We propose to use an approach to trust which takes into account a variety of aspects including location of sender, past behaviour, and reputation in other social networks. Our goal is to achieved the trust via relation and interaction between nodes in graph.
OBJECTIVE
- To study the trust theories in social network.
- To apply trust theory by using Gephi simulator.
- To identify the trust node in social network
METHODOLOGY
RESULT
By applying Popularity and Engagement trust theory, closeness centrality and betweenness centrality we can relate them with the result produced. Shown, node labelled Id 6" has the highest the closeness centrality and betweeness centrality which presented as the highly connected node in the network graph. Thus, node 6 is the most trusted node and anything that comes from node 6 (e.g. post on Facebook) is assumed to can trusted.
Conclusion
Trusted data from social network retrieved.