Social media are based on computer-mediated technologies that smooth the progress of the creation and distribution of information, thoughts, idea, career benefits and other forms of expression via implicit communities and networks. The social network analysis (SNA) has emerged with the increasing popularity of social networking services like Facebook, Twitter, etc. Therefore, information about group cohesion, contribution in activities, and associations among subjects can be obtained from the analysis of the blogs. The analysis of the blogs required well-known knowledge discovery tools to help the administrator to discover participant collaborative activities or patterns with inferences to improve the learning and sharing process. Therefore, the goal of this chapter is to provide the data mining tools for information retrieval, statistical modelling and machine learning to employ data pre-processing, data analysis, and data interpretation processes to support the use of social network analysis (SNA) to improve the collaborative activities for better performance.
TopBackground
Now a day, social networks became very popular due to increasing propagation and affordability of internet enabled devices such as personal computers, mobile devices and internet tablets. This is also a vital source of online interactions and contents sharing, assessments, subjectivity, influences, approaches, evaluation, feelings, observations. opinions and sentiments expressions in form of text, reviews, blogs, discussions, news, remarks, reactions, or some other document.
The authors used the data mining tools to mine patterns from social network data sites with advanced search results to understand the social data for research and organizational betterment.
User also takes the decisions, give opinions in a different form with very little or no restriction on information posted on social network. These view and opinion used by the organization for the betterment of their service.
There has been a lot of work done on as friend of a friend (FOAF) to look into how nearby and worldwide group level gatherings create and develop in substantial scale of social media platforms on the Semantic Web, Web administrations and online investigative affiliation.
It has been observed from the literature survey that most of authors described the data mining usage in the analysis of the social network sites data but what are techniques actual used to generate the meaningful information is not sated by most of the authors.
The main objective this paper is to show the data mining techniques used to generate the analyzed pattern from the social network data along with the implication and future scope of data mining in social network.