Social Network Analysis (SNA) tries to understand and exploit the key features of social networks in order to manage their life cycle and predict their evolution. Increasingly popular web 2.0 sites are forming huge social network. Classical methods from social network analysis (SNA) have been applied to such online networks. In this paper, we propose leveraging semantic web technologies to merg...

These days, most of companies expanding their business horizon through dynamic web sites based on Web 2.0 concept. The JavaScript is a key choice of web developers to build sophisticated dynamic web 2.0 application such social network site, blogs, e-commerce websites. On the other hand vulnerable JavaScript code is also exploited by the hackers to launch the attacks. Hacker may tamper the JavaS...

Social media operates in the online environment, and the challenge is to enhance the end-user experience. The chapter asserts that the consumer experience and behaviour in the online (e.g. e-commerce) and offline environments have some commonality with social media. Building a successful brand online is a prerequisite for success, but fundamental to trusting brand beliefs is the ability to crea...

Professor Pascal Poncelet talk was focused on analysis of data associate to social network. In his presentation, Professor Poncelet summarized several techniques through knowledge discovery on databases process. In this talk, doctor Roche outlined last tendencies in text mining task. Doctor Hacid presented a complete overview concerning techniques associated to explote social web data. Techniqu...

In the massive online worlds of social media, users frequently rely on organizing themselves around specific topics of interest to find and engage with like-minded people. However, navigating these massive worlds and finding topics of specific interest often proves difficult because the worlds are mostly organized haphazardly, leaving users to find relevant interests by word of mouth or using a...

Social networks have become a vital component in personal life. People are addicted to social network features, updating their profile page and collaborating virtually with other members have become daily routines. Social networks contain massive collection of data. Web data mining is a new trend in the current research body. This conceptual paper introduces a framework that can be used to mine...

Perhaps the fastest growing arena in the World Wide Web is the space of social networking sites (e.g., Friendster, Facebook, MySpace). The success of these sites directly depends on the number and activity level of their users. What attracts users to the site is a continually changing digital content (e.g., messages, pictures, photos, music, videos, blogs) generated by other users. In contrast,...