Title: Social Media Analysis based on Semanticity of Streaming and Batch Data,
Abstract: Languages shared by people differ in different regions based on their
accents, pronunciation and word usages. In this era sharing of language takes
place mainly through social media and blogs. Every second swing of such a micro
posts exist which induces the need of processing those micro posts, in-order to
extract knowledge out of it. Knowledge extraction differs with respect to the
application in which the research on cognitive science fed the necessities for
the same. This work further moves forward such a research by extracting
semantic information of streaming and batch data in applications like Named
Entity Recognition and Author Profiling. In the case of Named Entity
Recognition context of a single micro post has been utilized and context that
lies in the pool of micro posts were utilized to identify the sociolect aspects
of the author of those micro posts. In this work Conditional Random Field has
been utilized to do the entity recognition and a novel approach has been
proposed to find the sociolect aspects of the author (Gender, Age group).