With advanced digitalisation, we can observe a massive increase of user-generated content
on the web that provides opinions of people on different subjects. Sentiment analysis is the …

The analysis of the opinions of customers and users has been always of great interest in
supporting decision-making in many fields, especially in marketing. Sentiment analysis (SA) …

Accurate and reliable wind power forecasting has become very important to power system
scheduling and safely stable operating. In this paper, a novel self-attention temporal …

Due to the complex semantics of natural language, the multi-sentiment polarity of words, and
the long-dependence of sentiments between words, the existing sentiment analysis methods …

Urdu is a widely used language in South Asia and worldwide. While there are similar
datasets available in English, we created the first multi-label emotion dataset consisting of …

Sentiment analysis using stemmed Twitter data from various languages is an emerging
research topic. In this paper, we address three data augmentation techniques namely Shift …

The paper proposes an integrated speech emotion conversion framework developed using
speaker-independent mixed-lingual training. The key contribution of the work is non-parallel …

Aspect-level sentiment classification aims to identify the sentiment polarity of a specific
aspect in a sentence. In recent years, many researchers have sought to explore aspect …

Convolutional neural networks (CNN), recurrent neural networks (RNN), attention, and their
variants are extensively applied in the sentiment analysis, and the effect of fusion model is …

Aspect-based sentiment analysis (ABSA) is a fine-grained task which aims to identify the
emotional polarity of a specific aspect in a text or sentence. Aspect term extraction (ATE) …