Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6837675 | Computers in Human Behavior | 2016 | 6 Pages |
Abstract
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.
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Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Monireh Hosseini, Zohreh Tammimy,