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Guidance for Multi-Type Entity Graphs from Text Collections

Müller, Martin and Ballweg, Kathrin and Landesberger, Tatiana von and Yimam, Seid Muhie and Fahrer, Uli and Biemann, Chris and Rosenbach, Marcel and Regneri, Michaela and Ulrich, Heiner (2017):
Guidance for Multi-Type Entity Graphs from Text Collections.
pp. 1-5, EuroVA 2017 - 8th International EuroVis workshop on Visual Analytics, Barcelona, Spain, June 12.-13., 2017, DOI: 10.2312/eurova.20171111,
[Conference or Workshop Item]

Abstract

The visual exploration of graphs encoding relationships between entities of multiple types (e.g., persons, locations,...) supports journalists in finding newsworthy information in large text collections. Journalists may have interest in certain entity types or their relations such as locations or person-person relations. This interest may change during the exploration process. The exploration of such large graphs is often supported by guidance using a degree-of-interest (DOI) function. Although many DOIs exist, they do not differentiate entity types, rely on additional data, or require complex settings overburding the journalists. We present a novel DOI for graphs with multiple types of entities. We show the interesting subgraph around the focal node and offer information about possible further steps. The user can interactively set her interest in entity types and entity relations. We apply our approach to a graph extracted from WikiLeaks PlusD Cablegate documents and report on journalists' feedback.

Item Type: Conference or Workshop Item
Erschienen: 2017
Creators: Müller, Martin and Ballweg, Kathrin and Landesberger, Tatiana von and Yimam, Seid Muhie and Fahrer, Uli and Biemann, Chris and Rosenbach, Marcel and Regneri, Michaela and Ulrich, Heiner
Title: Guidance for Multi-Type Entity Graphs from Text Collections
Language: English
Abstract:

The visual exploration of graphs encoding relationships between entities of multiple types (e.g., persons, locations,...) supports journalists in finding newsworthy information in large text collections. Journalists may have interest in certain entity types or their relations such as locations or person-person relations. This interest may change during the exploration process. The exploration of such large graphs is often supported by guidance using a degree-of-interest (DOI) function. Although many DOIs exist, they do not differentiate entity types, rely on additional data, or require complex settings overburding the journalists. We present a novel DOI for graphs with multiple types of entities. We show the interesting subgraph around the focal node and offer information about possible further steps. The user can interactively set her interest in entity types and entity relations. We apply our approach to a graph extracted from WikiLeaks PlusD Cablegate documents and report on journalists' feedback.

Uncontrolled Keywords: Interaction, Visual analytics, Graphs, Digital humanities
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Event Title: EuroVA 2017 - 8th International EuroVis workshop on Visual Analytics
Event Location: Barcelona, Spain
Event Dates: June 12.-13., 2017
Date Deposited: 04 May 2020 12:16
DOI: 10.2312/eurova.20171111
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