"A SURVEY FOR THE PREDICTION OF AGE AND GENDER IN ONLINE SOCIAL NETWORKS"

Authors

Srilakshmi Mukkamala & Dr. G. Preethi (Assistant Professor)
Prist University, Thanjavur

Abstract

A common characteristic of communication on online social networks is that it happens via short messages, often using nonstandard language variations. These characteristics make this type of text a challenging text genre for natural language processing. Moreover, in these digital communities it is easy to provide a false name, age, gender and location in order to hide one’s true identity, providing criminals such as pedophiles with new possibilities to groom their victims. It would therefore be useful if user profiles can be checked on the basis of text analysis, and false profiles flagged for monitoring. This paper concerns with providing a detail survey to estimate age group and gender using data features also the age ranges are classified dynamically depending on number of groups using various classifier algorithm.