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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
Decades of scientific research have been conducted developing and evaluating methods for automated emotion recognition. There is now an extensive literature proposing and evaluating hundreds of different kinds of methods, leveraging techniques from multiple areas, such as signal processing, machine learning, computer vision, and speech processing.
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
Bidirectional encoder representations from transformers (BERT) is a language model introduced in October 2018 by researchers at Google. [1] [2] It learns to represent text as a sequence of vectors using self-supervised learning.
SemEval (Semantic Evaluation) is an ongoing series of evaluations of computational semantic analysis systems; it evolved from the Senseval word sense evaluation series. The evaluations are intended to explore the nature of meaning in language.
Hamka’s death came after Loughnane subjected her to what Justice Christopher Beale described as a "torrent of highly abusive text messages" in which he threatened to torture her, drown her, set ...
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 ]