Recognizing users gender in social media using linguistic features

Web 2.0 and social media provide users with an opportunity to discuss and share opinions, as a result, a considerable amount of information will emerge which can be drawn upon to determine some demographic and behavioral features.This study is an attempt to predict gender, as a demographic feature, using linguistic features of data collected from the users' comments in the social media.For this purpose, a framework is proposed to predict the users' gender by counting the number of some given words including verbs, pronouns, articles, adjectives, adverbs, preposition and numbers. This framework, thereafter, was tested using the comments that readers of Los Angeles Times left and the model were observed to predict the gender with an accuracy of 66.66%. Security solution and e-marketing can use this framework respectively for authentication and niche marketing. A framework is proposed to predict the users' gender in social media.We used the relationship between some linguistic features and users' gender in the framework.This framework was tested using the comments that readers of Los Angeles Times left.The model was observed to predict the gender with an accuracy of 66.66%.

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