Abstract Multimodal Entity-Based Sentiment Analysis (MEBSA) is an emerging task within
sentiment analysis, with the objective of simultaneously detecting entity, sentiment, and …

In this systematic review, Kitchenham's framework is used to explore what tasks, techniques,
and benchmarks for Sentiment Analysis have been developed for addressing topics about …

Abstract Machine learning and deep learning models are increasingly susceptible to
adversarial attacks, particularly in critical areas like cybersecurity and Information Disorder …

Nowadays, financial data from social media plays an important role to predict the stock
market. However, the exponential growth of financial information and the different polarities …

We conduct an inquiry into the sociotechnical aspects of sentiment analysis (SA) by critically
examining 189 peer-reviewed papers on their applications, models, and datasets. Our …

Entity-to-entity stance detection identifies the stance between a pair of entities with a
directed link that indicates the source, target and polarity. It is a streamlined task without the …

Abstract [eng] The analysis of emotions expressed in natural language text, also known as
sentiment analysis, is a key application of natural language processing (NLP). It involves …

Aspect-level sentiment analysis within multimodal contexts, focusing on the precise
identification and interpretation of sentiment attitudes linked to the target aspect across …

This paper explores the task of identifying the overall sentiment expressed towards volitional
entities (persons and organizations) in a document--what we refer to as Entity-Level …

The paper describes the RuSentNE-2023 evaluation devoted to targeted sentiment analysis
in Russian news texts. The task is to predict sentiment towards a named entity in a single …