Naslov
A Systematic Literature Review on Topic Modelling and Sentiment Analysis

Autori
Kunsabo, Josip ; Dobša, Jasminka

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of 33rd International Scientific Conference Central European Conference on Information and Intelligent Systems / Vrček, Neven ; Guardia, Lourdes ; Petra, Grd - Varaždin, 2022, 371-380

Skup
33rd Central European Conference on Information and Intelligent Systems (CECIIS 2022)

Mjesto i datum
Dubrovnik, Hrvatska, 21.09.2022. - 23.09.2022

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
topic modelling, sentiment analysis, machine learning, deep learning, sentiment lexicon

Sažetak
The human need for organization has always existed, but due to the ever-increasing generation of digital records, it is becoming almost necessary. With the development of information technologies, the use and application of various machine learning methods in the processing of natural language is becoming more widespread. In this paper we will give an overview of methods of topic modelling and sentiment analysis as well as approaches in processing of documents needed for their application. These two tasks of natural language processing are naturally related in the problem of identification of sentiments in the topics automatically extracted from the collection of observed documents.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti

POVEZANOST RADA