Workplace accidents in construction commonly cause fatal injury and fatality, resulting in
economic loss and negative social impact. Analysing accident description reports helps …

Improving user satisfaction by analyzing many user reviews found on e-commerce platforms
is becoming increasingly significant in this modern world. However, accurately predicting …

Purpose With the rise of social media platforms, an increasing number of cases of
cyberbullying has reemerged. Every day, large number of people, especially teenagers …

We propose a semi-supervised bootstrap learning framework for few-shot text classification.
From a small amount of the initial dataset, our framework obtains a larger set of reliable …

Coal chemical enterprises have many risk factors, and the causes of accidents are complex.
The traditional risk assessment methods rely on expert experience and previous literature to …

A sentiment lexicon is an important foundation for social network sentiment analysis.
However, in social networks, the sentiments of words vary with their topics of use, which …

Sentiment lexicon is used to judge the sentiments of words and plays a significant role in
sentiment analysis. Existing sentiment lexicons ignore the sentimental ambiguity of words in …

Education is an important domain that may be improved by analyzing the sentiments of
learners and educators. Evaluating the sustainability of the education system is critical for …

This research examined social media's role in understanding perceptions about the spaces
in which individuals interact, what planners can learn from social media data, and how to …

With the emergence and tremendous growth of text mining, a computer‐assisted approach
for capturing sentiment viewpoints from textual data is gradually becoming a promising field …