Machine learning for sentiment analysis: Opportunities and challenges
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Date
2022-05
Authors
Hua, Tianyu
Major Professor
Townsend, Anthony
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Rui, Chen
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Altmetrics
Abstract
With the advancements in artificial intelligence, mobile applications and start-ups for the emotional computing industry have grown rapidly. As one of the cornerstones of human-computer interaction, emotional intelligence is applied widely in the area of business communication, healthcare, distance education, safe driving, and public services. It is necessary for the current enterprise to deal with massive text data by using algorithms to extract and analyze the emotion expressed in the text. Machine learning helps apply sentiment analysis to text to show the attitude of positive, neutral, negative, or emotional judgments like happy, sad, angry, and other emotions (Borza, 2019). It would be beneficial to cut the business budget and manpower if the text could be turned into recognizable human attitudes by machines automatically.
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creative component
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2022