Quantum Criticism: A Tagged News Corpus Analysed for Sentiment and Named\n Entities

2020/06/05 by Ashwini Badgujar, Badgujar, Ashwini, Sheng Chen +9
Computer Science · Social Sciences · #Advanced Text Analysis Techniques #Authorship Attribution and Profiling #Computers and Society (cs.CY) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Misinformation and Its Impacts #Topic Modeling

paper · pdf · doi:10.48550/arxiv.2006.05267

openalex publication_date 2020/06/05 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28

Abstract

In this research, we continuously collect data from the RSS feeds of\ntraditional news sources. We apply several pre-trained implementations of named\nentity recognition (NER) tools, quantifying the success of each implementation.\nWe also perform sentiment analysis of each news article at the document,\nparagraph and sentence level, with the goal of creating a corpus of tagged news\narticles that is made available to the public through a web interface. Finally,\nwe show how the data in this corpus could be used to identify bias in news\nreporting.\n

Citations

• Race, gender, and the newsworthiness of homicide incidents
• News Coverage of the Gulf Crisis and Public Opinion

Related

• Experiments in News Bias Detection with Pre-Trained Neural Transformers
• SemCAFE: When Named Entities make the Difference Assessing Web Source Reliability through Entity-level Analytics
• Deep Learning for Digital Text Analytics: Sentiment Analysis
• Performance Comparison of Crowdworkers and NLP Tools on Named-Entity Recognition and Sentiment Analysis of Political Tweets
• SentiQNF: A Novel Approach to Sentiment Analysis Using Quantum Algorithms and Neuro-Fuzzy Systems