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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.
Network analysis, sentiment analysis 2004 (2015) [36] [37] Klimt, B. and Y. Yang Ling-Spam Dataset Corpus containing both legitimate and spam emails. Four version of the corpus involving whether or not a lemmatiser or stop-list was enabled. 2,412 Ham 481 Spam Text Classification 2000 [38] [39] Androutsopoulos, J. et al. SMS Spam Collection Dataset
Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words.
Sentiment analysis – extracts subjective information usually from a set of documents, often using online reviews to determine "polarity" about specific objects. It is especially useful for identifying trends of public opinion in the social media, for the purpose of marketing.
This example shows Chernoff faces for lawyers' ratings of twelve judges. Chernoff faces, invented by applied mathematician, statistician and physicist Herman Chernoff in 1973, display multivariate data in the shape of a human face. The individual parts, such as eyes, ears, mouth and nose represent values of the variables by their shape, size ...
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.
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 ...