TASKS AND METHODS OF TEXT SENTIMENT ANALYSIS

The purpose of this article is to study one of the methods of social networks analysis – text sentiment analysis. Today, social media has become a big data base that social network analysis is used for various purposes – from setting up targeted advertising for a cosmetics store to preventing riots...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autor principal:	А. Mukasheva
Formato:	article
Lenguaje:	EN
Publicado:	Astana IT University 2021
Materias:	sentiment analysis, opinion, aspect, unstructured text, structured data, classification Information technology T58.5-58.64
Acceso en línea:	https://doaj.org/article/a4b2e2fa32334f8cb24cd748ee3b41c6
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:a4b2e2fa32334f8cb24cd748ee3b41c6
record_format	dspace
spelling	oai:doaj.org-article:a4b2e2fa32334f8cb24cd748ee3b41c62021-12-02T13:00:20ZTASKS AND METHODS OF TEXT SENTIMENT ANALYSIS2707-90312707-904Xhttps://doaj.org/article/a4b2e2fa32334f8cb24cd748ee3b41c62021-10-01T00:00:00Zhttp://ojs.astanait.edu.kz/index.php/sjaitu/article/view/87https://doaj.org/toc/2707-9031https://doaj.org/toc/2707-904XThe purpose of this article is to study one of the methods of social networks analysis – text sentiment analysis. Today, social media has become a big data base that social network analysis is used for various purposes – from setting up targeted advertising for a cosmetics store to preventing riots at the state level. There are various methods for analyzing social networks such as graph method, text sentiment analysis, audio, and video object analysis. Among them, sentiment analysis is widely used for political, social, consumer research, and also for cybersecurity. Since the analysis of the sentiment of the text involves the analysis of the emotional opinions expressed in the text, the first step is to define the term opinion. An opinion can be simple, that is, a positive, negative or neutral emotion towards a particular object or its aspect. Comparison is also an opinion, but devoid of emotional connotation. To work with simple opinions, the first task of text sentiment analysis is to classify the text. There are three levels of classifications: classification at the text level, at the level of a sentence, and at the aspect level of the object. After classifying the text at the desired level, the next task is to extract structured data from unstructured information. The problem can be solved using the five-tuple method. One of the important elements of a tuple is the aspect in which an opinion is usually expressed. Next, aspect-based sentiment analysis is applied, which involves identifying aspects of the desired object and assessing the polarity of mood for each aspect. This task is divided into two sub-tasks such as aspect extraction and aspect classification. Sentiment analysis has limitations such as the definition of sarcasm and difficulty of working with abbreviated words.А. MukashevaAstana IT Universityarticlesentiment analysis, opinion, aspect, unstructured text, structured data, classificationInformation technologyT58.5-58.64ENScientific Journal of Astana IT University, Vol 7, Iss 7, Pp 55-62 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	sentiment analysis, opinion, aspect, unstructured text, structured data, classification Information technology T58.5-58.64
spellingShingle	sentiment analysis, opinion, aspect, unstructured text, structured data, classification Information technology T58.5-58.64 А. Mukasheva TASKS AND METHODS OF TEXT SENTIMENT ANALYSIS
description	The purpose of this article is to study one of the methods of social networks analysis – text sentiment analysis. Today, social media has become a big data base that social network analysis is used for various purposes – from setting up targeted advertising for a cosmetics store to preventing riots at the state level. There are various methods for analyzing social networks such as graph method, text sentiment analysis, audio, and video object analysis. Among them, sentiment analysis is widely used for political, social, consumer research, and also for cybersecurity. Since the analysis of the sentiment of the text involves the analysis of the emotional opinions expressed in the text, the first step is to define the term opinion. An opinion can be simple, that is, a positive, negative or neutral emotion towards a particular object or its aspect. Comparison is also an opinion, but devoid of emotional connotation. To work with simple opinions, the first task of text sentiment analysis is to classify the text. There are three levels of classifications: classification at the text level, at the level of a sentence, and at the aspect level of the object. After classifying the text at the desired level, the next task is to extract structured data from unstructured information. The problem can be solved using the five-tuple method. One of the important elements of a tuple is the aspect in which an opinion is usually expressed. Next, aspect-based sentiment analysis is applied, which involves identifying aspects of the desired object and assessing the polarity of mood for each aspect. This task is divided into two sub-tasks such as aspect extraction and aspect classification. Sentiment analysis has limitations such as the definition of sarcasm and difficulty of working with abbreviated words.
format	article
author	А. Mukasheva
author_facet	А. Mukasheva
author_sort	А. Mukasheva
title	TASKS AND METHODS OF TEXT SENTIMENT ANALYSIS
title_short	TASKS AND METHODS OF TEXT SENTIMENT ANALYSIS
title_full	TASKS AND METHODS OF TEXT SENTIMENT ANALYSIS
title_fullStr	TASKS AND METHODS OF TEXT SENTIMENT ANALYSIS
title_full_unstemmed	TASKS AND METHODS OF TEXT SENTIMENT ANALYSIS
title_sort	tasks and methods of text sentiment analysis
publisher	Astana IT University
publishDate	2021
url	https://doaj.org/article/a4b2e2fa32334f8cb24cd748ee3b41c6
work_keys_str_mv	AT amukasheva tasksandmethodsoftextsentimentanalysis
_version_	1718393584376348672

TASKS AND METHODS OF TEXT SENTIMENT ANALYSIS

Ejemplares similares