Analysis of Human Behavior by Mining Textual Data: Current Research Topics and Analytical Techniques

被引：4

作者：

Gutierrez, Edgar ^{[1
,2
]}

Karwowski, Waldemar ^{[1
]}

Fiok, Krzysztof ^{[1
]}

Davahli, Mohammad Reza ^{[1
]}

Liciaga, Tameika ^{[1
]}

Ahram, Tareq ^{[1
]}

机构：

[1] Univ Cent Florida, Dept Ind Engn & Management Syst, Orlando, FL 32816 USA

[2] MIT, Global SCALE, LOGyCA, Ctr Latin Amer Logist Innovat, Bogota 110111, Colombia

来源：

SYMMETRY-BASEL | 2021年 / 13卷 / 07期

关键词：

text mining; human behavior; sentiment analysis; physiological profiling; LANGUAGE; PERSONALITY; FEEDBACK; WORDS;

D O I：

10.3390/sym13071276

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The goal of this study was to conduct a literature review of current approaches and techniques for identifying, understanding, and predicting human behaviors through mining a variety of sources of textual data with a focus on enabling classification of psychological behaviors regarding emotion, cognition, and social empathy. This review was performed using keyword searches in ISI Web of Science, Engineering Village Compendex, ProQuest Dissertations, and Google Scholar. Our findings show that, despite recent advancements in predicting human behaviors based on unstructured textual data, significant developments in data analytics systems for identification, determination of interrelationships, and prediction of human cognitive, emotional and social behaviors remain lacking.

引用

页数：22

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