Text Sentiment Analysis Based on Convolutional Neural Network and Bidirectional LSTM ModelText sentiment analysis is used to discover the public's appreciation and preferences for specific events. In order to effectively extract the deep semantic features of sentences and reduce the dependence of long ...
The process of sentiment analysis of Chinese micro-blog topic based on the sentiment dictionary is shown in Fig. 1. The method we proposed mainly includes two aspects: The rest of the paper is organized as follows: In Section 2, we give a brief review of related works about sentiment ...
Meena et al. [21] propose a sentiment analysis-based POI recommendation system using NLP techniques to predict sentiment polarities from user content. The study combines BiLSTM for sentiment prediction and LSTM for recommending POIs, achieving superior accuracy (99.52%) on thefoursquare datasetand o...
In this paper, we propose an innovative MSA model called a text-based multimodal fusion network with multi-scale feature extraction and unsupervised contrastive learning for multimodal sentiment analysis (TMFN). The model utilizes convolutional kernels of different sizes to capture the multi-scale featu...
A significant number of literature and research have been developed about text-based emotion detection. Emotion detection is an expanded version of sentiment analysis. In order to determine the sentiments of tweets, a BERT architecture incorporating CNN, RNN, and Bi-LSTM was assessed on the Twitter...
Joint Multimodal Aspect-based Sentiment Analysis (JMASA) is a significant task in the research of multimodal fine-grained sentiment analysis, which combines two subtasks: Multimodal Aspect Term Extraction (MATE) and Multimodal Aspect-oriented Sentiment Classification (MASC). Currently, most existing ...
without using any pre-definedsentiment lexica or polarity shifting rules. Wealso evaluate the model’s ability to predict sentiment distributions on a new dataset basedon confessions from the experience project. The dataset consists of personal user storiesannotated with multiple labels which, whenaggreg...
Previous studies combine the Long Short-Term Memory (LSTM) and attention mechanism to predict the sentiment polarity of the given aspect category, but the LSTM-based methods are not really bidirectional text feature extraction methods. In this paper, we propose a multi-task aspect-category ...
The primary objective of this research is to investigate Efficient Text Analysis using Bidirectional Encoder Representations from Transformers (BERT) Based for Named Entity Recognition and Classification in the Malayalam language. To conduct Named Entity Recognition (NER) in the Malayalam dialect, which ...
Machine Learning + LSTM Implementation to capture sentiments surrouding the Colombian elections in 2018. Sentiment analysis entirely on Spanish tweets with interesting external data sourcing. machine-learning sentiment-analysis keras naive-bayes-classifier spanish-tweets textgeneration Updated Jun 19, 2018...