Gender Identification Through Facebook Data Analysis Using Machine Learning Techniques

被引：3

作者：

Kiratsa, P. I. ^{[1
]}

Sidiropoulos, G. K. ^{[1
]}

Badeka, E. V. ^{[1
]}

Papadopoulou, C. I. ^{[1
]}

Nikolaou, A. P. ^{[1
]}

Papakostas, G. A. ^{[1
]}

机构：

[1] Eastern Macedonia & Thrace Inst Technol, HUMAIN Lab, Dept Comp & Informat, Kavala, Greece

来源：

22ND PAN-HELLENIC CONFERENCE ON INFORMATICS (PCI 2018) | 2018年

关键词：

gender identification; facebook profile; machine learning methods; data mining techniques; social networks;

D O I：

10.1145/3291533.3291591

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The purpose of this paper is to analyze Facebook users' profile aiming at identifying the gender of the profile's owner. To this end several machine learning models were adopted and applied on a representative set of features extracted from Facebook profiles describing users' preferences relative to their gender information. This study concludes that there is a plethora of features which can be mined from a Facebook profile and can be used in identifying the gender of a profile's owner. Moreover, the experiments reveal that this gender identification task can be accomplished effectively by using machine learning techniques with 97.30% accuracy, after considering a large amount of Facebook profile data.

引用

页码：117 / 120

页数：4

共 50 条

[21] A Support Vector Machine-Based Gender Identification Using Speech Signal
Lee, Kye-Hwan
Kang, Sang-Ick
Kim, Deok-Hwan
Chang, Joon-Hyuk
IEICE TRANSACTIONS ON COMMUNICATIONS, 2008, E91B (10) : 3326 - 3329
[22] Understanding Customers Using Facebook Pages: Data Mining Users Feedback Using Text Analysis
Wu, Hsin-Ying
Liu, Kuan-Liang
Trappey, Charles
PROCEEDINGS OF THE 2014 IEEE 18TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD), 2014, : 346 - 350
[23] Gender Identification Using Marginalised Stacked Denoising Autoencoders on Twitter Data
Al-onazi, Badriyya B.
Nour, Mohamed K.
Alshamrani, Hassan
Al Duhayyim, Mesfer
Mohsen, Heba
Abdelmageed, Amgad Atta
Mohammed, Gouse Pasha
Zamani, Abu Sarwar
INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2023, 36 (03) : 2529 - 2544
[24] A Brief Survey for MicroRNA Precursor Identification Using Machine Learning Methods
Guan, Zheng-Xing
Li, Shi-Hao
Zhang, Zi-Mei
Zhang, Dan
Yang, Hui
Ding, Hui
CURRENT GENOMICS, 2020, 21 (01) : 11 - 25
[25] Human face gender identification using Thepade's sorted N-ary block truncation coding and machine learning classifiers
Thepade, Sudeep D.
Abin, Deepa
Das, Rik
Sarode, Tanuja
INTERNATIONAL JOURNAL OF INTELLIGENT ENGINEERING INFORMATICS, 2020, 8 (02) : 77 - 94
[26] REAL-TIME SENTIMENT ANALYSIS ON SOCIAL NETWORKS USING META-MODEL AND MACHINE LEARNING TECHNIQUES
Xiao, Shixiao
Alobaedy, Mustafa Muwafak
Goyal, S. B.
Singla, Sanjay
Kang, Sandeep
Chadha, Raman
SCALABLE COMPUTING-PRACTICE AND EXPERIENCE, 2023, 24 (04): : 819 - 834
[27] Predicting Firms' Performances in Customer Complaint Management Using Machine Learning Techniques
Peker, Serhat
INTELLIGENT AND FUZZY SYSTEMS: DIGITAL ACCELERATION AND THE NEW NORMAL, INFUS 2022, VOL 2, 2022, 505 : 280 - 287
[28] Gender identification for Egyptian Arabic dialect in twitter using deep learning models
ElSayed, Shereen
Farouk, Mona
EGYPTIAN INFORMATICS JOURNAL, 2020, 21 (03) : 159 - 167
[29] The Impact of using Social Network on Academic Performance by using Contextual and Localized Data Analysis of Facebook Groups
Aqeel, Muhammad
Pasha, Mukarram
Saeed, Muhammad
Nishat, Muhammad Kamran
Feroz, Maryam
Siddiqui, Farhan Ahmed
Touheed, Nasir
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2019, 10 (12) : 397 - 402
[30] A Comparative Study on Speaker Gender Identification Using MFCC and Statistical Learning Methods
Xiao, Hanguang
PROCEEDINGS OF INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY (CSAIT 2013), 2014, 255 : 715 - 723

← 1 2 3 4 5 →