A survey on sentiment analysis methods, applications, and challenges

M Wankhade, ACS Rao, C Kulkarni - Artificial Intelligence Review, 2022‏ - Springer
The rapid growth of Internet-based applications, such as social media platforms and blogs,
has resulted in comments and reviews concerning day-to-day activities. Sentiment analysis …

The evolution of topic modeling

R Churchill, L Singh - ACM Computing Surveys, 2022‏ - dl.acm.org
Topic models have been applied to everything from books to newspapers to social media
posts in an effort to identify the most prevalent themes of a text corpus. We provide an in …

[HTML][HTML] Is text preprocessing still worth the time? A comparative survey on the influence of popular preprocessing methods on Transformers and traditional classifiers

M Siino, I Tinnirello, M La Cascia - Information Systems, 2024‏ - Elsevier
With the advent of the modern pre-trained Transformers, the text preprocessing has started
to be neglected and not specifically addressed in recent NLP literature. However, both from …

A novel LSTM–CNN–grid search-based deep neural network for sentiment analysis

I Priyadarshini, C Cotton - The Journal of Supercomputing, 2021‏ - Springer
As the number of users getting acquainted with the Internet is escalating rapidly, there is
more user-generated content on the web. Comprehending hidden opinions, sentiments, and …

Machine learning techniques for emotion detection and sentiment analysis: current state, challenges, and future directions

A Alslaity, R Orji - Behaviour & Information Technology, 2024‏ - Taylor & Francis
Emotion detection and Sentiment analysis techniques are used to understand polarity or
emotions expressed by people in many cases, especially during interactive systems use …

A comprehensive survey on word representation models: From classical to state-of-the-art word representation language models

U Naseem, I Razzak, SK Khan, M Prasad - Transactions on Asian and …, 2021‏ - dl.acm.org
Word representation has always been an important research area in the history of natural
language processing (NLP). Understanding such complex text data is imperative, given that …

Double embeddings and CNN-based sequence labeling for aspect extraction

H Xu, B Liu, L Shu, PS Yu - arxiv preprint arxiv:1805.04601, 2018‏ - arxiv.org
One key task of fine-grained sentiment analysis of product reviews is to extract product
aspects or features that users have expressed opinions on. This paper focuses on …

[ספר][B] Machine learning for text: An introduction

CC Aggarwal, CC Aggarwal - 2018‏ - Springer
The extraction of useful insights from text with various types of statistical algorithms is
referred to as text mining, text analytics, or machine learning from text. The choice of …

Current state of text sentiment analysis from opinion to emotion mining

A Yadollahi, AG Shahraki, OR Zaiane - ACM Computing Surveys (CSUR …, 2017‏ - dl.acm.org
Sentiment analysis from text consists of extracting information about opinions, sentiments,
and even emotions conveyed by writers towards topics of interest. It is often equated to …

Understanding customer satisfaction via deep learning and natural language processing

Á Aldunate, S Maldonado, C Vairetti… - Expert Systems with …, 2022‏ - Elsevier
It is of utmost importance for marketing academics and service industry practitioners to
understand the factors that influence customer satisfaction. This study proposes a novel …