Comparative Analysis of Statistical Classifiers for Predicting News Popularity on Social Web

Chopra, Aman; Dimri, Ashray; Rawat, Sumanu

doi:10.1109/iccci.2019.8822230

Cited by 3 publications

(2 citation statements)

References 4 publications

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“…In another related study, the authors used the Valence Aware Dictionary and sEntiment Reasoner (VADER) tool as a simple rule-based model for general sentiment analysis [15]. The VADER tool uses both qualitative and quantitative methods to analyze and validate data.…”

Section: Related Workmentioning

confidence: 99%

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FADOHS: Framework for Detection and Integration of Unstructured Data of Hate Speech on Facebook Using Sentiment and Emotion Analysis

Rodriguez

Argueta²

2022

IEEE Access

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Hate speech is a form of expression that assaults a person or a community based on race, origin, religion, sexual orientation, or other attributes. Although it can be expressed in multiple ways online and offline, the increasing popularity of social media has exponentially increased both its use and severity. The target of this research, therefore, is to locate and analyze the unstructured data of chosen social media posts that intend to spread hate in the comment sections. To do so, we propose a novel framework based on data science tools, with the objective of sensitizing all social media providers to the pervasiveness of hate on social media. We use sentiment and emotion algorithms to analyze recent posts and comments on those pages. Posts suspected of containing dehumanizing words are preprocessed before being fed to a K-means clustering algorithm, one of the simplest and most popular unsupervised machine learning methods. The proposed framework for automatic detection of hate speech (FADOHS) surpasses the most recent methods identified in A Survey on Automatic Detection of Hate Speech in Text in terms of precision, recall, and F1 scores by 10%.

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Section: Related Workmentioning

confidence: 99%

“…We also use the VADER tool for sentiment analysis. However, unlike the research in [15], we incorporate the JAMMIN tool to perform emotional analysis experiments and, specifically, track posts with negative comments. The research [8] creates a typology of abhorrence based on different "loathing levels."…”

Section: Related Workmentioning

confidence: 99%