There is an exponential growth in textual content generation every day in today's world. In-
app messaging such as Telegram and WhatsApp, social media websites such as Instagram …

Sentiment analysis in conversations has gained increasing attention in recent years for the
growing amount of applications it can serve, eg, sentiment analysis, recommender systems …

Persona attribute extraction is critical for personalized human-computer interaction.
Dialogue is an important medium that communicates and delivers persona information …

Depression is increasingly prevalent, leading to higher suicide risk. Depression detection
and sentimental analysis of text inputs in cross-domain frameworks are challenging. Solo …

Text classification is one of the fundamental tasks in natural language processing, which
requires an agent to determine the most appropriate category for input sentences. Recently …

Multimodal cross-domain sentiment analysis aims at transferring domain-invariant sentiment
information across datasets to address the insufficiency of labeled data. Existing adaptation …

We investigate cross-lingual sentiment analysis, which has attracted significant attention due
to its applications in various areas including market research, politics, and social sciences …

Sentiment analysis (SA), and emotion detection and recognition from text (EDRT) are recent
areas of study that are closely related to each other. Sentiment analysis strives to identify …

Standard machine learning and deep learning architectures have been widely used in the
field of sentiment analysis, but their performance is unsatisfactory if the input texts are short …

The representation of words as vectors, conventionally known as word embeddings, has
drawn considerable attention in recent years as feature learning techniques for natural …