Age classification from Spanish tweets the variable age analyzed by using linear classifiers

Text classification or text categorization in social networks such as Twitter has taken great importance with the growth of applications of this process in diverse domains of society. Literature about text classifiers is significantly wide especially in languages such as English; however, this is not the case for age classification whose studies have been mainly focused on image recognition and analysis. This paper presents the results of testing linear classifiers performance in the task of identifying Twitter users age from their profile descriptions and tweets. For this purpose, a Spanish Lexicon of 45 words around the concept "cumpleaños" was created and the Gold Standard of 1541 users with age correctly identified was obtained. The experiments are presented with the description of the algorithms used to finally obtain the best seven models that permit to identify the user's age with accuracy results between 66% and 69 %. Considering the information-retrieval layer, the new results showed that accuracy was increased from 69,09% to 72,96%.