Social data in digital form—including user-generated content, expressed or implicit relations
between people, and behavioral traces—are at the core of popular applications and …

The task of quantification consists in providing an aggregate estimation (eg, the class
distribution in a classification problem) for unseen test sets, applying a model that is trained …

In this paper we present two deep-learning systems that competed at SemEval-2017 Task 4
“Sentiment Analysis in Twitter”. We participated in all subtasks for English tweets, involving …

The evolution of green industrial policy in China is deeply embedded within a unique
political, economic, cultural, and social milieu. The intricacies and complexities inherent in …

Social media plays a pivotal role in the daily activities of individuals, serving as a medium for
the dissemination of events, activities, and information through various forms of posts …

This open access book provides an introduction and an overview of learning to quantify (aka
“quantification”), ie the task of training estimators of class proportions in unlabeled data by …

Quantification is the task of estimating, given a set σ σ of unlabelled items and a set of
classes C={c_ 1, ..., c_| C|\} C= c 1,…, c| C|, the prevalence (or “relative frequency”) in σ σ of …

Sentiment analysis is the process of extracting the opinions of customers from online
reviews. In general, customers express their reviews in natural language. It becomes a …

In this study, we focus on understanding and mining user's preferences and intentions via
user-based aggregation in the context of a social network. Understanding preference and …

In the era of web 2.0, online forums, blogs and Twitter are becoming primary sources for
sharing views, opinions and comments about different topics. Classifying these views …