We introduce XED, a multilingual fine-grained emotion dataset. The dataset consists of
human-annotated Finnish (25k) and English sentences (30k), as well as projected …

We present first results of the project “Emotions in Drama” in which we explore the
annotation of emotions and the application of computational emotion analysis …

In this paper, we present first work-in-progress annotation results of a project investigating
computational methods of emotion analysis for historical German plays around 1800. We …

Sentiment analysis and opinion mining are essential tasks with many prominent application
areas, eg, when researching popular opinions on products or brands. Sentiments expressed …

This paper introduces a gamified framework for fine-grained sentiment analysis and emotion
detection. We present a flexible tool, Sentimentator, that can be used for efficient annotation …

This paper is a pilot study that aims to explore the viability of annotation projection from one
language to another as well as to evaluate the multilingual data set we have created for …

Poorly annotated data is a common problem for data-intensive applications like supervised
machine learning. In domains like healthcare, annotation tasks require specific domain …

Gamification has been applied to many linguistic annotation tasks, as an alternative to
crowdsourcing platforms to collect annotated data in an inexpensive way. However, we think …

In the era of digital intelligence empowerment, the data-driven approach to the mining and
organization of humanistic knowledge has ushered in new development opportunities …

We present the results of a comparative evaluation study of five annotation tools with 50
participants in the context of sentiment and emotion annotation of literary texts. Ten …