Identifying User Demographic Traits through Virtual-World Language Use
نویسندگان
چکیده
The paper presents approaches to identifying realworld demographic attributes based on language use in the virtual world. We apply features developed from the classic literature on sociolinguistics and sound symbolism to data collected from virtual-world chat and avatar naming to determine participants’ age and gender. We also examine participants’ use of avatar names across virtual worlds and how these names are employed to project a consistent identity across environments, which we call “traveling characteristics.” Keywords—virtual worlds, linguistic features, machine learning
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