Social networks occupy a ubiquitous and pervasive place in the life of their users. The
substantial amount of content generated and shared by social networking users offers new …

Social networking sites such as Facebook or Twitter attract millions of users, who everyday
post an enormous amount of content in the form of tweets, comments and posts. Since social …

Short-texts accentuate the challenges posed by the high feature space dimensionality of text
learning tasks. The linked nature of social data causes new dimensions to be added to the …

Large-scale text categorisation in social environments, characterised by the high
dimensionality of feature spaces, is one of the most relevant problems in machine learning …

The aim of this systematic review is to determine the current state of the art in the real-time
classification of user-generated content from social media. Focus is on the identification of …

In this survey, we review different text mining techniques to discover various textual patterns
from the social networking sites. Social network applications create opportunities to …

With the rapid growth of social Web applications such as Twitter and online advertisements,
the task of understanding short texts is becoming more and more important. Most traditional …

Most natural language processing work has been on world languages like English, but most
people in the world speak other languages that are comparatively poorly resourced in terms …

Social media such as blogs, Facebook, Twitter, YouTube and Flickr enables people of all
walks of life to express their thoughts, voice their opinions, and connect to each other more …

Abstract Online Social Network's (OSN) considered a spark that burst the Big Data era. The
unfolding of every event, breaking new or trend flows in real time inside OSN triggering a …