Evaluation and sociolinguistic analysis of text features for gender and age identification

Simaki Vasiliki; Mporas Iosif; Megalooikonomou Vasileios

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Evaluation and sociolinguistic analysis of text features for gender and age identification

机译：文本特征的评估和社会语言分析，以识别性别和年龄

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摘要

The paper presents an interdisciplinary study in the field of automatic gender and age identification, under the scope of sociolinguistic knowledge on gendered and age linguistic choices that social media users make. The authors investigated and gathered standard and novel text features used in text mining approaches on the author’s demographic information and profiling and they examined their efficacy in gender and age detection tasks on a corpus consisted of social media texts. An analysis of the most informative features is attempted according to the nature of each feature and the information derived after the characteristics’ score of importance is discussed.

机译：本文在社会语言用户对性别和年龄语言选择做出的社会语言知识的范围内，提出了在性别和年龄自动识别领域的跨学科研究。作者调查并收集了用于文本挖掘方法的标准和新颖文本功能，以用于作者的人口统计学信息和配置文件，并研究了它们在由社交媒体文本组成的语料库中对性别和年龄检测任务的功效。根据每个特征的性质尝试对信息最丰富的特征进行分析，并讨论在特征的重要性得分之后得出的信息。

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来源
《American journal of engineering and applied sciences》 |2016年第4期|868-876|共9页
作者
Simaki Vasiliki; Mporas Iosif; Megalooikonomou Vasileios;
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作者单位

Department of Computer Science, Linnaeus University, Växjö, Sweden,Centre for Language and Literature, Lund University, Lund, Sweden;

School of Engineering and Technology, University of Hertfordshire, Hatfield, United Kingdom;

Multidimensional Data Analysis and Knowledge Management Laboratory, Dept. Of Computer Engineering and Informatics, University of Patras, Rion, Greece;

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原文格式 PDF
正文语种 eng
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关键词
Age identification; Feature ranking; Gender detection; ReliefF algorithm; Sociolinguistics; Text mining;

机译：年龄识别;功能排名;性别检测;ReliefF算法;社会语言学;文字挖掘;

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Evaluation and sociolinguistic analysis of text features for gender and age identification

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