Logo des Repositoriums
 

Visualization Needs in Computational Social Sciences

dc.contributor.authorHeuer, Hendrik
dc.contributor.authorPolizzotto, Anna
dc.contributor.authorMarx, Franziska
dc.contributor.authorBreiter, Andreas
dc.contributor.editorAlt, Florian
dc.contributor.editorBulling, Andreas
dc.contributor.editorDöring, Tanja
dc.date.accessioned2019-08-22T04:36:37Z
dc.date.available2019-08-22T04:36:37Z
dc.date.issued2019
dc.description.abstractWith the advent of digital humanities and computational social sciences, machine learning techniques like topic modeling are increasingly employed by social scientists and humanities scholars. This poses the question what visualization needs these researchers have when confronted with such complex systems. In this paper, we investigate visualization needs in the context of the topic modeling algorithm Latent Dirichlet Allocation and the 950,000 articles of the New York Times corpus. We presented visualizations of how the topics in the newspaper changed over time to seven participants, who fulfilled three tasks with three visualization types. Qualitative interviews with the participants supported our assumptions that visualizations for these tasks need to be visually appealing, intuitively interpretable, and minimizing mental effort.en
dc.description.urihttps://dl.acm.org/authorize?N681272
dc.identifier.doi10.1145/3340764.3344440
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/24614
dc.language.isoen
dc.publisherACM
dc.relation.ispartofMensch und Computer 2019 - Tagungsband
dc.relation.ispartofseriesMensch und Computer
dc.subjectVisualization
dc.subjectStacked Area Chart
dc.subjectStacked Bar Chart
dc.subjectHeat Map
dc.subjectLatent Dirichlet Allocation
dc.titleVisualization Needs in Computational Social Sciencesen
dc.typeText/Conference Paper
gi.citation.publisherPlaceNew York
gi.conference.date8.-11. September 2019
gi.conference.locationHamburg
gi.conference.sessiontitleMCI: Short Paper (Poster)
gi.document.qualitydigidoc

Dateien

Originalbündel
1 - 1 von 1
Lade...
Vorschaubild
Name:
poster-392.pdf
Größe:
779.42 KB
Format:
Adobe Portable Document Format