“Tidal Trust” is an algorithm which is developed under “Trust on the Semantic Web” project by Jennifer Golbeck. According to this project social network data that represented using the FOAF vocabulary, are the most prevalent data on semantic web. Jennifer Golbeck presented “Tidal Trust” and a network analysis of its foundation in her work on “Personalizing Applications through Integration of Inferred Trust Values in Semantic Web-base Social Networks. Here we will present a summary on it.
“Social Networks” have become the source of most prevalent data over semantic web. A lot of Scholars are researching on the data of social network to make it better and proposing new algorithms that may help users around the world to stay nearer to the information or connection he needs. There is a project named “FOAF” which stands for “The Friends of a Friend”. It’s created for creating a scope for analyzing data of social network as it is in real ones. There is more than 8,000,000 simulated people’s information for research purpose. Any researcher can access and use them to compute and test his application.
Trust among the connections in the social networks became an important issue now. Suggestions for new connections, groups, pages, news and may be interesting advertisements are being displayed on users’ walls and profiles based on some intelligent algorithms. Most of these algorithms computes users’ connections and activities and make useful things displayed over pages of social networks. Some tremendous algorithms are invented by Scholars of different parts of the world. Among them Jennifer Golbeck is one of them. She has proposed one of the most intelligent algorithm on inferring trusts relationships in the semantic Web-based social networks. The algorithm she proposed is known as “Tidal Trust” and there are two existing application in which this algorithm is used, they are “FilmTrust” and “TrustMail”.
Semantic Web (http://infomesh.net/2001/swintro/)
The Semantic Web is a mesh of information linked up in such a way as to be easily processable by machines, on a global scale. You can think of it as being an efficient way of representing data on the World Wide Web, or as a globally linked database.
The Semantic Web was thought up by Tim Berners-Lee, inventor of the WWW, URIs, HTTP, and HTML. There is a dedicated team of people at the World Wide Web consortium (W3C) working to improve, extend and standardize the system, and many languages, publications, tools and so on have already been developed. However, Semantic Web technologies are still very much in their infancies, and although the future of the project in general appears to be bright, there seems to be little consensus about the likely direction and characteristics of the early Semantic Web.
What's the rationale for such a system? Data that is geneally hidden away in HTML files is often useful in some contexts, but not in others. The problem with the majority of data on the Web that is in this form at the moment is that it is difficult to use on a large scale, because there is no global system for publishing data in such a way as it can be easily processed by anyone. For example, just think of information about local sports events, weather information, plane times, Major League Baseball statistics, and television guides... all of this information is presented by numerous sites, but all in HTML. The problem with that is that, is some contexts, it is difficult to use this data in the ways that one might want to do so.
So the Semantic Web can be seen as a huge engineering solution... but it is more than that. We will find that as it becomes easier to publish data in a repurposable form, so more people will want to pubish data, and there will be a knock-on or domino effect. We may find that a large number of Semantic Web applications can be used for a variety of different tasks, increasing the modularity of applications on the Web. But enough subjective reasoning... onto how this will be accomplished.
The Semantic Web is generally built on syntaxes which use URIs to represent data, usually in triples based structures: i.e. many triples of URI data that can be held in databases, or interchanged on the world Wide Web using a set of particular syntaxes developed especially for the task. These syntaxes are called "Resource Description Framework" syntaxes.
Social Network (http://en.wikipedia.org/wiki/Social_network)
A social network is a theoretical construct useful in the social sciences to study relationships between individuals, groups, organizations, or even entire societies (social units, see differentiation). The term is used to describe a social structure determined by such interactions. The ties (sometimes called edges, links, or connections) in the structure are called "nodes". The nodes through which any given social unit connects represent the convergence of the various social contacts of that unit. Many kinds of relationships may form the "network" between such nodes, but interpersonal "bridges" are a defining characteristic of social networks. Social network approaches are useful for modeling and explaining many social phenomena. The theoretical approach is, necessarily, relational. An axiom of the social network approach to understanding social interaction is that social phenomena should be primarily conceived and investigated through the properties of relations between and within units, instead of the properties of these units themselves. Thus, one common criticism of social network theory is that individual agency is essentially ignored, although this is not the case in practice (see agent-based modeling). Precisely because many different types of relations, singular or in combination, form into a network configuration, network analytics are useful to a broad range of research enterprises. In social science, these fields of study include, but are not limited to anthropology, biology, communication studies, economics, geography, information science, organizational studies, social psychology, sociology, and sociolinguistics. Scholars in these and other areas have used the idea of "social network" loosely for almost a century to connote complex sets of relationships between members of social units across all scales of analysis, from the local to the global as well as the scale-free.