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Artigo em Inglês | MEDLINE | ID: mdl-34379592


We present VisInReport, a visual analytics tool that supports the manual analysis of discourse transcripts and generates reports based on user interaction. As an integral part of scholarly work in the social sciences and humanities, discourse analysis involves an aggregation of characteristics identified in the text, which, in turn, involves a prior identification of regions of particular interest. Manual data evaluation requires extensive effort, which can be a barrier to effective analysis. Our system addresses this challenge by augmenting the users' analysis with a set of automatically generated visualization layers. These layers enable the detection and exploration of relevant parts of the discussion supporting several tasks, such as topic modeling or question categorization. The system summarizes the extracted events visually and verbally, generating a content-rich insight into the data and the analysis process. During each analysis session, VisInReport builds a shareable report containing a curated selection of interactions and annotations generated by the analyst. We evaluate our approach on real-world datasets through a qualitative study with domain experts from political science, computer science, and linguistics. The results highlight the benefit of integrating the analysis and reporting processes through a visual analytics system, which supports the communication of results among collaborating researchers.

IEEE Comput Graph Appl ; 38(6): 26-38, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30668453


For the past two years, researchers from the visualization community and the digital humanities have come together at the IEEE VIS conference to discuss how both disciplines can work together to push research goals in their respective disciplines. In this paper, we present our experiences as a result of this collaboration.