Abstract: Social Network Analysis

Abstract-- Social network analysis (SNA) is a social structure of people interacts to each other through common interest of network and graph theories. It characterizes networked structures in terms of nodes, ties or edges (relationships or interactions) that connect them. Netvizz and gephi is a tool used to detect the data in facebook account for large datasets. Big data is used to describe a massive volume of both structured and unstructured data that is so large and difficult to process using traditional database and software techniques. This paper addresses the research problem of identifying the degree of separation from a different viewpoint by considering not only the degree of separation between two normal-persons or famous-persons,

Search engine developers are always striving to deliver search results that are relevant to the search query being processed. Consistent with this goal, there have been attempts to rank search results based on a number of different factors. One of the more popular ways to rank search results involves analyzing the location and frequency of keywords on a web page. Another frequently used technique is analyzing how web pages link to each other. A web page gets a ranking boost based on the number of other web pages that are linked to it. Click-through rates of search results are analyzed in some search engines. The general rule is: the higher the click-through rate, the higher the ranking. A search result may also be marked based on its click history. In one embodiment, a search result is marked with an image or a text string if there was a single click on the search result by a friend of the member who submitted the query. In other embodiments, the frequency of clicks by members of social network who are within a predetermined degree of separation from the member who submitted the query is examined. If such frequency exceeds a minimum value, the associated search result is marked with an image or a text string. Social ties are increasingly constructed and maintained by online social networking tools. These online tools provide an alternative to the more traditional physical

Edges can be either directed or undirected graph in a network. Adjacency list and adjacency matrix are used to represent edges in network formation. It helps to connect average shortest path length and high clustering. In social network graph can connect two people nodes and to check the account maintained by user in dataset. It matches with the user account and to generate a graph in gephi. [B]Dataset identification: The dataset will be preprocessed based on experiments to check the value and filter out the invalid data. The filtering function was responsible for participant’s account information in order to delete all fake acccount’s.It will minimize the influence from invalid data and the accuracy of our experiment. The graph database is analyzed based on graph of real facebook users who used our “We R So Close Tool “that represents the account in actual individuals.

[C]data storage: A hierarchical database is organized into a tree-like structure. The data is stored as records which are connected through links in another database. It contains the collection of fields and records in multiple relationships. It may handle all the unstructured data in a structured