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Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.
Multimodal sentiment analysis is a technology for traditional text-based sentiment analysis, which includes modalities such as audio and visual data. [1] It can be bimodal, which includes different combinations of two modalities, or trimodal, which incorporates three modalities. [ 2 ]
In other words, data analysis is the phase that takes filtered data as input and transforms that into information of value to the analysts. Many different types of analysis can be performed with social media data, including analysis of posts, sentiment, sentiment drivers, geography, demographics, etc. The data analysis step begins once we know ...
Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. [1] It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties , edges , or links (relationships or interactions) that connect them.
Social media such as Facebook, X are also combined to predict elections via sentiment analysis. [127] Additional social media (e.g. YouTube, Google Trends ) can be combined to reach a wider segment of the voting population, minimise media-specific bias, and inexpensively estimate electoral predictions which are on average half of a percentage ...
Public opinion, also called sentiment; Sentimentality, an appeal to shallow, uncomplicated emotions at the expense of reason; Sentimental novel, an 18th-century literary genre; Market sentiment, optimism or pessimism in financial and commodity markets; Sentiment analysis, automatic detection of opinions embodied in text
Research on using Twitter in education has been conducted by Dr. Reynol Junco and his colleagues. Using a controlled experimental design with random assignment, they found that classroom use of Twitter in specific ways such as continuing course discussions outside of class led to significant increases in student engagement and grades for all of their courses. [15]
In machine learning, kernel machines are a class of algorithms for pattern analysis, whose best known member is the support-vector machine (SVM). These methods involve using linear classifiers to solve nonlinear problems. [1]
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