Humans are increasingly integrated with devices that enable the collection of vast
unstructured opinionated data. Accurately analysing subjective information from this data is …

Cross-lingual sentiment analysis (CLSA) leverages one or several source languages to help
the low-resource languages to perform sentiment analysis. Therefore, the problem of lack of …

Today's text classifiers inevitably suffer from unintended dataset biases, especially the
document-level label bias and word-level keyword bias, which may hurt models' …

To bridge the knowledge gap between research and practice, we present the first empirical
study on 16,500 the most popular Android apps, demystifying how smartphone apps exploit …

Hate speech is an increasingly important societal issue in the era of digital communication.
Hateful expressions often make use of figurative language and, although they represent, in …

Sentiment analysis is an area of study that aims to develop computational methods and tools
to extract and classify the opinions and emotions expressed by people on social networks …

Deep learning (DL) becomes increasingly pervasive, being used in a wide range of software
applications. These software applications, named as DL based software (in short as DL …

Deep learning (DL) is moving its step into a growing number of mobile software applications.
These software applications, named as DL based mobile applications (abbreviated as …

Due to the diversity and variability of Chinese syntax and semantics, accurately identifying
and distinguishing individual emotions from online texts is challenging. To overcome this …

Due to their on-body and ubiquitous nature, wearables can generate a wide range of unique
sensor data creating countless opportunities for deep learning tasks. We propose …