DROPS

Document

Visual Text Analytics (Dagstuhl Seminar 22191)

Authors: Christopher Collins, Antske Fokkens, Andreas Kerren, Chris Weaver, and Angelos Chatzimparmpas

Published in: Dagstuhl Reports, Volume 12, Issue 5 (2022)

Abstract

Text data is one of the most abundant types of data available, produced every day across all domains of society. Understanding the contents of this data can support important policy decisions, help us understand society and culture, and improve business processes. While machine learning techniques are growing in their power for analyzing text data, there is still a clear role for human analysis and decision-making. This seminar explored the use of visual analytics applied to text data as a means to bridge the complementary strengths of people and computers. The field of visual text analytics applies visualization and interaction approaches which are tightly coupled to natural language processing systems to create analysis processes and systems for examining text and multimedia data. During the seminar, interdisciplinary working groups of experts from visualization, natural language processing, and machine learning examined seven topic areas to reflect on the state of the field, identify gaps in knowledge, and create an agenda for future cross-disciplinary research. This report documents the program and the outcomes of Dagstuhl Seminar 22191 "Visual Text Analytics".

Cite as

Christopher Collins, Antske Fokkens, Andreas Kerren, Chris Weaver, and Angelos Chatzimparmpas. Visual Text Analytics (Dagstuhl Seminar 22191). In Dagstuhl Reports, Volume 12, Issue 5, pp. 37-91, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

Copy BibTex To Clipboard

@Article{collins_et_al:DagRep.12.5.37,
  author =	{Collins, Christopher and Fokkens, Antske and Kerren, Andreas and Weaver, Chris and Chatzimparmpas, Angelos},
  title =	{{Visual Text Analytics (Dagstuhl Seminar 22191)}},
  pages =	{37--91},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2022},
  volume =	{12},
  number =	{5},
  editor =	{Collins, Christopher and Fokkens, Antske and Kerren, Andreas and Weaver, Chris and Chatzimparmpas, Angelos},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.12.5.37},
  URN =		{urn:nbn:de:0030-drops-174432},
  doi =		{10.4230/DagRep.12.5.37},
  annote =	{Keywords: Information visualization, visual text analytics, visual analytics, text visualization, explainable ML for text analytics, language models, text mining, natural language processing}
}

Document

DOI: 10.4230/OASIcs.CMN.2014.241

Finding Stories in 1,784,532 Events: Scaling Up Computational Models of Narrative

Authors: Marieke van Erp, Antske Fokkens, and Piek Vossen

Published in: OASIcs, Volume 41, 2014 Workshop on Computational Models of Narrative

Abstract

Information professionals face the challenge of making sense of an ever increasing amount of information. Storylines can provide a useful way to present relevant information because they reveal explanatory relations between events. In this position paper, we present and discuss the four main challenges that make it difficult to get to these stories and our first ideas on how to start resolving them.

Cite as

Marieke van Erp, Antske Fokkens, and Piek Vossen. Finding Stories in 1,784,532 Events: Scaling Up Computational Models of Narrative. In 2014 Workshop on Computational Models of Narrative. Open Access Series in Informatics (OASIcs), Volume 41, pp. 241-245, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

Copy BibTex To Clipboard

@InProceedings{vanerp_et_al:OASIcs.CMN.2014.241,
  author =	{van Erp, Marieke and Fokkens, Antske and Vossen, Piek},
  title =	{{Finding Stories in 1,784,532 Events: Scaling Up Computational Models of Narrative}},
  booktitle =	{2014 Workshop on Computational Models of Narrative},
  pages =	{241--245},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-71-2},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{41},
  editor =	{Finlayson, Mark A. and Meister, Jan Christoph and Bruneau, Emile G.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2014.241},
  URN =		{urn:nbn:de:0030-drops-46601},
  doi =		{10.4230/OASIcs.CMN.2014.241},
  annote =	{Keywords: big data, news, aggregation, story detection}
}

Search Results

Documents authored by Fokkens, Antske

Visual Text Analytics (Dagstuhl Seminar 22191)

Abstract

Cite as

Finding Stories in 1,784,532 Events: Scaling Up Computational Models of Narrative

Abstract

Cite as

Thanks for your feedback!

Could not send message