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A survey on sentiment analysis methods, applications, and challenges
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 …
has resulted in comments and reviews concerning day-to-day activities. Sentiment analysis …
The evolution of topic modeling
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 …
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
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 …
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
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 …
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
Emotion detection and Sentiment analysis techniques are used to understand polarity or
emotions expressed by people in many cases, especially during interactive systems use …
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
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 …
language processing (NLP). Understanding such complex text data is imperative, given that …
Double embeddings and CNN-based sequence labeling for aspect extraction
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 …
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 …
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
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 …
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
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 …
understand the factors that influence customer satisfaction. This study proposes a novel …