Analyzing Sentiment and Determining Negation Scope in Political News - S, Padmaja; Bandu, Sasidhar; Ganu, Deepa; S, Sameen Fatima (International Journal of Computer Sciences and Engineering, 2019)
Automatic detection of linguistic negation in free text is a demanding need for many text processing applications including sentiment analysis. Our system uses online news archives from two different resources namely NDTV and The Hindu to predict the scope of negation in the text. In this paper, our main focus was on identifying the scope of negation in news articles for two political parties namely YSR Congress Party (YSRCP) and Alliance (which includes Jana Sena Party, Communist Party of India , Bahujan Samaj Party , Telugu Desam Party (TDP)) by using two existing namely Fixed Window Length (FWL), Dependency Analysis (DA) and one proposed methodology is Negation Sentiment Analyzer (NSA). The average F measures for each one of them were 0.61, 0.66 and 0.72 respectively. It was observed that NSA outperforms the other two. We further evaluated the results of NSA against the standard BioScope negation corpus as a benchmark, achieving 0.75 as a F1 scores.