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Application of Machine Learning and Deep Learning in Sentiment Analysis
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Application of Machine Learning and Deep Learning in Sentiment Analysis

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Questions and Answers

What is sentiment analysis?

The computer study of people's attitudes, views, feelings, and emotions as they are represented in written language.

Why has sentiment analysis become one of the most active study fields in text mining and natural language processing?

Opinions are fundamental to practically all human endeavors, and they are significant determinants of our behaviors, leading to a wide variety of applications.

What are the two key causes of the appeal of sentiment analysis?

Opinions being fundamental to human endeavors and significant determinants of behaviors, and the presence of difficult research challenges that had never been tried before the year 2000.

What is the significance of the availability of opinionated text in digital forms for sentiment analysis research?

<p>The lack of opinionated text available in digital forms prior to the year 2000 contributed to the lack of research in sentiment analysis.</p> Signup and view all the answers

What are the research challenges associated with sentiment analysis prior to the year 2000?

<p>There weren't many opinionated text available in digital forms, leading to a lack of research in sentiment analysis.</p> Signup and view all the answers

Define sentiment analysis in your own words.

<p>Sentiment analysis is the process of analyzing and understanding people's emotions, attitudes, views, and feelings as expressed in written language.</p> Signup and view all the answers

What are the major areas of study that have expanded to include research on sentiment analysis?

<p>Management sciences and social sciences</p> Signup and view all the answers

What is the specific emphasis of the sentiment analysis in the learning objectives?

<p>Finding sentiments associated with sadness</p> Signup and view all the answers

What are some of the emotions that need to be classified in the sentiment analysis?

<p>Joy, sadness, fear, anger, surprise</p> Signup and view all the answers

What methods are required for efficient strategies in removing identified elements from Twitter comments?

<p>Data pre-treatment and natural language processing (NLP) methods</p> Signup and view all the answers

What is the focus of multimodal sentiment analysis?

<p>Examining sentiments communicated through text, graphics, and voice</p> Signup and view all the answers

What is the purpose of integrating and fusing data from several modalities in sentiment analysis?

<p>To perform thorough sentiment analysis</p> Signup and view all the answers

What is the importance of recognizing effective methods for combining and aligning data from various sources in sentiment analysis?

<p>Efficient sentiment analysis across several modalities</p> Signup and view all the answers

Name some of the multimodal model architectures mentioned in the text for sentiment analysis.

<p>Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Bidirectional LSTMs (BiLSTMs), and other deep learning models</p> Signup and view all the answers

What technology connects millions of people through microblogging platforms?

<p>Social media</p> Signup and view all the answers

What type of messages do people communicate on microblogging platforms?

<p>Brief messages known as tweets</p> Signup and view all the answers

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