Detection of Reading Absorption in User-Generated Book Reviews: Resources Creation and Evaluation

To detect how and when readers are experiencing engagement with a literary work, we bring together empirical literary studies and
language technology via focusing on the affective state of absorption. The goal of our resource development is to enable the detection
of different levels of reading absorption in millions of user-generated reviews hosted on social reading platforms. We present a corpus
of social book reviews in English that we annotated with reading absorption categories. Based on these data, we performed supervised,

Linguistic Appropriateness and Pedagogic Usefulness of Reading Comprehension Questions

Automatic generation of reading comprehension questions is a topic receiving growing interest in the NLP community, but there is currently no consensus on evaluation metrics and many approaches focus on linguistic quality only while ignoring the pedagogic value and appropriateness of questions. This paper overcomes such weaknesses by a new evaluation scheme where questions from the questionnaire are structured in a hierarchical way to avoid confronting human annotators with evaluation measures that do not make sense for a certain question.

Annotation guidelines for the Fact-Ita Bank Negation corpus

Fact-Ita Bank for FactA@EVALITA 2016 has been enriched with a new level of annotation, namely negation cues, their scope and their focus. Here we present the guidelines for negation information annotation.


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