A survey of text mining in social media facebook and twitter perspectives

Text mining has become one of the trendy fields that has been incorporated in several research fields such as computational linguistics, Information Retrieval (IR) and data mining. Natural Language Processing (NLP) techniques were used to extract knowledge from the textual text that is written by hu...

Full description

Bibliographic Details
Main Authors:	Said A., Salloum, Mostafa, Al-Emran, Azza, Abdel Monem, Khaled, Shaalan
Format:	Article
Language:	English
Published:	2017
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/17141/ http://umpir.ump.edu.my/id/eprint/17141/ http://umpir.ump.edu.my/id/eprint/17141/1/A%20survey%20of%20text%20mining%20in%20social%20media%20facebook%20and%20twitter%20perspectives.pdf

id	ump-17141
recordtype	eprints
spelling	ump-171412017-08-28T07:35:57Z http://umpir.ump.edu.my/id/eprint/17141/ A survey of text mining in social media facebook and twitter perspectives Said A., Salloum Mostafa, Al-Emran Azza, Abdel Monem Khaled, Shaalan TK Electrical engineering. Electronics Nuclear engineering Text mining has become one of the trendy fields that has been incorporated in several research fields such as computational linguistics, Information Retrieval (IR) and data mining. Natural Language Processing (NLP) techniques were used to extract knowledge from the textual text that is written by human beings. Text mining reads an unstructured form of data to provide meaningful information patterns in a shortest time period. Social networking sites are a great source of communication as most of the people in today’s world use these sites in their daily lives to keep connected to each other. It becomes a common practice to not write a sentence with correct grammar and spelling. This practice may lead to different kinds of ambiguities like lexical, syntactic, and semantic and due to this type of unclear data, it is hard to find out the actual data order. Accordingly, we are conducting an investigation with the aim of looking for different text mining methods to get various textual orders on social media websites. This survey aims to describe how studies in social media have used text analytics and text mining techniques for the purpose of identifying the key themes in the data. This survey focused on analyzing the text mining studies related to Facebook and Twitter; the two dominant social media in the world. Results of this survey can serve as the baselines for future text mining research. 2017 Article PeerReviewed application/pdf en cc_by http://umpir.ump.edu.my/id/eprint/17141/1/A%20survey%20of%20text%20mining%20in%20social%20media%20facebook%20and%20twitter%20perspectives.pdf Said A., Salloum and Mostafa, Al-Emran and Azza, Abdel Monem and Khaled, Shaalan (2017) A survey of text mining in social media facebook and twitter perspectives. Advances in Science, Technology and Engineering Systems Journal, 2 (1). pp. 127-133. ISSN 2415-6698 https://www.researchgate.net/profile/Said_Salloum/publication/313075362_A_Survey_of_Text_Mining_in_Social_Media_Facebook_and_Twitter_Perspectives/links/588f82f592851c9794c471cf/A-Survey-of-Text-Mining-in-Social-Media-Facebook-and-Twitter-Perspectives.pdf
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Said A., Salloum Mostafa, Al-Emran Azza, Abdel Monem Khaled, Shaalan A survey of text mining in social media facebook and twitter perspectives
description	Text mining has become one of the trendy fields that has been incorporated in several research fields such as computational linguistics, Information Retrieval (IR) and data mining. Natural Language Processing (NLP) techniques were used to extract knowledge from the textual text that is written by human beings. Text mining reads an unstructured form of data to provide meaningful information patterns in a shortest time period. Social networking sites are a great source of communication as most of the people in today’s world use these sites in their daily lives to keep connected to each other. It becomes a common practice to not write a sentence with correct grammar and spelling. This practice may lead to different kinds of ambiguities like lexical, syntactic, and semantic and due to this type of unclear data, it is hard to find out the actual data order. Accordingly, we are conducting an investigation with the aim of looking for different text mining methods to get various textual orders on social media websites. This survey aims to describe how studies in social media have used text analytics and text mining techniques for the purpose of identifying the key themes in the data. This survey focused on analyzing the text mining studies related to Facebook and Twitter; the two dominant social media in the world. Results of this survey can serve as the baselines for future text mining research.
format	Article
author	Said A., Salloum Mostafa, Al-Emran Azza, Abdel Monem Khaled, Shaalan
author_facet	Said A., Salloum Mostafa, Al-Emran Azza, Abdel Monem Khaled, Shaalan
author_sort	Said A., Salloum
title	A survey of text mining in social media facebook and twitter perspectives
title_short	A survey of text mining in social media facebook and twitter perspectives
title_full	A survey of text mining in social media facebook and twitter perspectives
title_fullStr	A survey of text mining in social media facebook and twitter perspectives
title_full_unstemmed	A survey of text mining in social media facebook and twitter perspectives
title_sort	survey of text mining in social media facebook and twitter perspectives
publishDate	2017
url	http://umpir.ump.edu.my/id/eprint/17141/ http://umpir.ump.edu.my/id/eprint/17141/ http://umpir.ump.edu.my/id/eprint/17141/1/A%20survey%20of%20text%20mining%20in%20social%20media%20facebook%20and%20twitter%20perspectives.pdf
first_indexed	2023-09-18T22:23:26Z
last_indexed	2023-09-18T22:23:26Z
_version_	1777415809233059840

A survey of text mining in social media facebook and twitter perspectives

Similar Items