Sentiment analysis of Twitter data during critical events through Bayesian networks classifiers
Sentiment analysis through machine learning using Twitter data has become a popular topic
in recent years. Here we address the problem of sentiment analysis during critical events …
in recent years. Here we address the problem of sentiment analysis during critical events …
Sentiment analysis for the natural environment: A systematic review
In this systematic review, Kitchenham's framework is used to explore what tasks, techniques,
and benchmarks for Sentiment Analysis have been developed for addressing topics about …
and benchmarks for Sentiment Analysis have been developed for addressing topics about …
An efficient hybrid filter and evolutionary wrapper approach for sentiment analysis of various topics on Twitter
Sentiment Analysis is currently considered as one of the most attractive research topics in
Natural Language Processing (NLP) field. The main objective of sentiment analysis is to …
Natural Language Processing (NLP) field. The main objective of sentiment analysis is to …
Long short term memory (LSTM) model for sentiment analysis in social data for e-commerce products reviews in Hindi languages
Sentiment analysis has become an important tool for e-commerce giant to capture user
sentiment towards their product and to exploit such analysis to attract user for buying …
sentiment towards their product and to exploit such analysis to attract user for buying …
Transformer-based approach towards music emotion recognition from lyrics
The task of identifying emotions from a given music track has been an active pursuit in the
Music Information Retrieval (MIR) community for years. Music emotion recognition has …
Music Information Retrieval (MIR) community for years. Music emotion recognition has …
A case study of Spanish text transformations for twitter sentiment analysis
Sentiment analysis is a text mining task that determines the polarity of a given text, ie, its
positiveness or negativeness. Recently, it has received a lot of attention given the interest in …
positiveness or negativeness. Recently, it has received a lot of attention given the interest in …
[PDF][PDF] Aspect-based sentiment classification with attentive neural turing machines.
Aspect-based sentiment classification aims to identify sentiment polarity expressed towards
a given opinion target in a sentence. The sentiment polarity of the target is not only highly …
a given opinion target in a sentence. The sentiment polarity of the target is not only highly …
Using a hybrid-classification method to analyze Twitter data during critical events
In this paper, sentiment analysis of two critical events is presented using machine learning
(ML) techniques. COVID-19 has put immense pressure across the globe and sentiment …
(ML) techniques. COVID-19 has put immense pressure across the globe and sentiment …
An improved machine learning technique for identify informative COVID-19 tweets
S Malla, PJA Alphonse - … Journal of System Assurance Engineering and …, 2022 - Springer
Twitter users are increasingly using the platform to share information, particularly in the case
of disease outbreaks such as COVID-19. It's difficult to find informative tweets about …
of disease outbreaks such as COVID-19. It's difficult to find informative tweets about …
Twitter sentiment analysis with different feature extractors and dimensionality reduction using supervised learning algorithms
Twitter is an online micro-blogging platform which allows us to treasure trove about the
current circumstance at any juncture in time. In this paper, we analyze the sentiments of …
current circumstance at any juncture in time. In this paper, we analyze the sentiments of …