Deep learning for sentiment analysis: A survey
Deep learning has emerged as a powerful machine learning technique that learns multiple
layers of representations or features of the data and produces state‐of‐the‐art prediction …
layers of representations or features of the data and produces state‐of‐the‐art prediction …
[HTML][HTML] A survey on deep learning for textual emotion analysis in social networks
S Peng, L Cao, Y Zhou, Z Ouyang, A Yang, X Li… - Digital Communications …, 2022 - Elsevier
Abstract Textual Emotion Analysis (TEA) aims to extract and analyze user emotional states
in texts. Various Deep Learning (DL) methods have developed rapidly, and they have …
in texts. Various Deep Learning (DL) methods have developed rapidly, and they have …
Recent trends in deep learning based natural language processing
Deep learning methods employ multiple processing layers to learn hierarchical
representations of data, and have produced state-of-the-art results in many domains …
representations of data, and have produced state-of-the-art results in many domains …
[책][B] Sentiment analysis: Mining opinions, sentiments, and emotions
B Liu - 2020 - books.google.com
Sentiment analysis is the computational study of people's opinions, sentiments, emotions,
moods, and attitudes. This fascinating problem offers numerous research challenges, but …
moods, and attitudes. This fascinating problem offers numerous research challenges, but …
Aspect based twitter sentiment analysis on vaccination and vaccine types in covid-19 pandemic with deep learning
Due to the COVID-19 pandemic, vaccine development and community vaccination studies
are carried out all over the world. At this stage, the opposition to the vaccine seen in the …
are carried out all over the world. At this stage, the opposition to the vaccine seen in the …
Topic-level sentiment analysis of social media data using deep learning
Due to the inception of Web 2.0 and freedom to facilitate the dissemination of information,
sharing views, expressing opinions with regards to current world level events, services …
sharing views, expressing opinions with regards to current world level events, services …
[HTML][HTML] A semantic similarity-based perspective of affect lexicons for sentiment analysis
Lexical resources are widely popular in the field of Sentiment Analysis, as they represent a
resource that directly encodes sentimental knowledge. Usually sentiment lexica are used for …
resource that directly encodes sentimental knowledge. Usually sentiment lexica are used for …
Refining word embeddings using intensity scores for sentiment analysis
Word embeddings that provide continuous low-dimensional vector representations of words
have been extensively used for various natural language processing tasks. However …
have been extensively used for various natural language processing tasks. However …
Attention-based long short-term memory network using sentiment lexicon embedding for aspect-level sentiment analysis in Korean
M Song, H Park, K Shin - Information Processing & Management, 2019 - Elsevier
Although deep learning breakthroughs in NLP are based on learning distributed word
representations by neural language models, these methods suffer from a classic drawback …
representations by neural language models, these methods suffer from a classic drawback …
Deep learning for religious and continent-based toxic content detection and classification
With time, numerous online communication platforms have emerged that allow people to
express themselves, increasing the dissemination of toxic languages, such as racism …
express themselves, increasing the dissemination of toxic languages, such as racism …