This research proposed an algorithm and method for sentiment analysis using both text and emoticon. In this work, both modes of data were analyzed in combined and separately with both machine learning and deep learning algorithms for finding sentiments from twitter based airline data using several ...
An efficient approach for sentiment analysis using machine learning algorithmSemantic analysisMachine learning algorithmsPreprocessingAccuracyOptimizationSentimental analysis determines the views of the user from the social media. It is used to classify the content of the text into neutral, negative and ...
This paper mainly present an interpretable neural net framework for financial sentiment analysis. First, it designed a hierarchical model to learn the representation of a document from multiple granularities. Specifically it built representations of sentences from individual words and then aggregate those...
Sentiment analysisSupport Vector Machine (SVM)Complex sentence patternClassificationWith the development of Web2.0 era, as local information publishing and social networking platform of Twitter, microblog has become an important medium for people to share and propagate information. Sentiment classification ...
Sentiments, evaluations, attitudes, and emotions are the subjects of study of sentiment analysis and opinion mining. The inception and rapid growth of the field coincide with those of the social media on the Web, e.g., reviews, forum discussions, blogs, micro blogs, Twitter, and social networ...
Natural language processing and machine translation –They work on parsing human language, enabling tasks like sentiment analysis, chatbot functionalities, and language translation. Recommender systems –They create personalized recommendation engines for e-commerce platforms or entertainment sites like Netflix...
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B.By using sentiment analysis. C.By writing summaries. D.By consulting critics and audiences.【小题2】What is the key factor for a successful movie according to the researchers? A.A happy ending. B.Famous movie stars. C.A well-known producer. D.Frequent sentiment changes.【小题3】What ...
The non-linear, unsupervised t-distributed Stochastic Neighbor Embedding (t-SNE) is typically employed for data analysis and high-dimensional data visualization. For all the selected datasets, t-SNE plots obtained by KCGWO, GMM, and K-means are plotted in Figs. 5, 6, 7, 8, 9, 10, 11 ...
The Amazon SageMaker AI BlazingText algorithm provides highly optimized implementations of the Word2vec and text classification algorithms. The Word2vec algorithm is useful for many downstream natural language processing (NLP) tasks, such as sentiment analysis, named entity recognition, machine translation...