Thesis (M.Sc.) - Cairo University - Faculty of Computer and Information - Department of Information Systems

Nowadays social networks are considered the fastest and the most important communication method which help persons or users to interact, exchange and communicate together from di erent countries. Social networks connect peo- ple from di erent places through online websites such as Facebook. Social networks analysis methods help in getting valuable insights for social net- works such as election by clustering the social networks' users, in industrial domain such as online branding pages or online advertising. Social networks analysis has two main urgent research gaps, the rst is community detection which helps in clustering or dividing the complex network into a set of clusters or groups, while the second is nding an accurate social network prediction approach for predicting posts' e ciency and performance for Facebook such as number of likes, shares and the interactions with audience

Issued also as CD