Abstract
Complexity of event data in texts makes
it difficult to assess its content, espe-
cially when considering larger collections
in which different sources report on the
same or similar situations.
We present
a system that makes it possible to visually analyze complex event and emotion
data extracted from texts. We show that
we can abstract from different data models for events and emotions to a single data
model that can show the complex relations
in four dimensions. The visualization has
been applied to analyze 1) dynamic devel-
opments in how people both conceive and
express emotions in theater plays and 2)
how stories are told from the perspective
of their sources based on rich event data
extracted from news or biographies.
it difficult to assess its content, espe-
cially when considering larger collections
in which different sources report on the
same or similar situations.
We present
a system that makes it possible to visually analyze complex event and emotion
data extracted from texts. We show that
we can abstract from different data models for events and emotions to a single data
model that can show the complex relations
in four dimensions. The visualization has
been applied to analyze 1) dynamic devel-
opments in how people both conceive and
express emotions in theater plays and 2)
how stories are told from the perspective
of their sources based on rich event data
extracted from news or biographies.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the workshop NLP meets Journalism |
| Place of Publication | Copenhagen, Denmark |
| Pages | 37-45 |
| Number of pages | 9 |
| Publication status | Published - 2017 |
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