Investigating Institutional Bias Through a Visualization Dashboard

Gabriel Canelo Vilaseca; Angelos Chatzimparmpas

doi:10.1109/VAST-Challenge69463.2025.00019

Investigating Institutional Bias Through a Visualization Dashboard

Gabriel Canelo Vilaseca^*
, Angelos Chatzimparmpas

^*Corresponding author for this work

Sub Visualisation and Graphics

Utrecht University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

In this work, we present an interactive data visualization dashboard developed for the 2025 VAST Challenge Mini-Challenge 2, which investigates stakeholder engagement and potential bias during council meetings. The dashboard integrates matrix-based visualizations, barplots, trend lines, boxplots, and tooltips to support exploratory analysis. Through the TROUT (tourism) and FILAH (fishing) datasets, we identify systematic sentiment differences aligned with each group’s sectoral interests—particularly when discussions involve their own industries (e.g., large-vessel fishing or tourism)—providing evidence of potential bias among council members (COOTEFOO). Incorporating the JOURNALIST dataset, which combines both perspectives, reveals a moderation of sentiment extremes when a broader, more balanced view is introduced. Overall, this paper demonstrates how interactive dashboards can effectively expose and contextualize institutional bias, underscoring the utility of data-driven approaches for transparency.

Original language	English
Title of host publication	Proceedings - 2025 IEEE Visual Analytics Science and Technology, VAST Challenge 2025
Publisher	IEEE
Pages	29-30
Number of pages	2
ISBN (Electronic)	979-8-3315-9090-1
DOIs	https://doi.org/10.1109/VAST-Challenge69463.2025.00019
Publication status	Published - 23 Dec 2025
Event	2025 IEEE Visual Analytics Science and Technology, VAST Challenge 2025 - Vienna, Australia Duration: 3 Nov 2025 → 3 Nov 2025

Conference

Conference	2025 IEEE Visual Analytics Science and Technology, VAST Challenge 2025
Country/Territory	Australia
City	Vienna
Period	3/11/25 → 3/11/25

Bibliographical note

Publisher Copyright:
©2025 IEEE.

Keywords

Bias Detection
Data Visualization Dashboard
Matrix-Based Visualization
Mini-Challenge 2
VAST Challenge

Access to Document

10.1109/VAST-Challenge69463.2025.00019

Cite this

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title = "Investigating Institutional Bias Through a Visualization Dashboard",

abstract = "In this work, we present an interactive data visualization dashboard developed for the 2025 VAST Challenge Mini-Challenge 2, which investigates stakeholder engagement and potential bias during council meetings. The dashboard integrates matrix-based visualizations, barplots, trend lines, boxplots, and tooltips to support exploratory analysis. Through the TROUT (tourism) and FILAH (fishing) datasets, we identify systematic sentiment differences aligned with each group{\textquoteright}s sectoral interests—particularly when discussions involve their own industries (e.g., large-vessel fishing or tourism)—providing evidence of potential bias among council members (COOTEFOO). Incorporating the JOURNALIST dataset, which combines both perspectives, reveals a moderation of sentiment extremes when a broader, more balanced view is introduced. Overall, this paper demonstrates how interactive dashboards can effectively expose and contextualize institutional bias, underscoring the utility of data-driven approaches for transparency.",

keywords = "Bias Detection, Data Visualization Dashboard, Matrix-Based Visualization, Mini-Challenge 2, VAST Challenge",

author = "Vilaseca, \{Gabriel Canelo\} and Angelos Chatzimparmpas",

note = "Publisher Copyright: {\textcopyright}2025 IEEE.; 2025 IEEE Visual Analytics Science and Technology, VAST Challenge 2025 ; Conference date: 03-11-2025 Through 03-11-2025",

year = "2025",

month = dec,

day = "23",

doi = "10.1109/VAST-Challenge69463.2025.00019",

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T1 - Investigating Institutional Bias Through a Visualization Dashboard

AU - Vilaseca, Gabriel Canelo

AU - Chatzimparmpas, Angelos

PY - 2025/12/23

Y1 - 2025/12/23

N2 - In this work, we present an interactive data visualization dashboard developed for the 2025 VAST Challenge Mini-Challenge 2, which investigates stakeholder engagement and potential bias during council meetings. The dashboard integrates matrix-based visualizations, barplots, trend lines, boxplots, and tooltips to support exploratory analysis. Through the TROUT (tourism) and FILAH (fishing) datasets, we identify systematic sentiment differences aligned with each group’s sectoral interests—particularly when discussions involve their own industries (e.g., large-vessel fishing or tourism)—providing evidence of potential bias among council members (COOTEFOO). Incorporating the JOURNALIST dataset, which combines both perspectives, reveals a moderation of sentiment extremes when a broader, more balanced view is introduced. Overall, this paper demonstrates how interactive dashboards can effectively expose and contextualize institutional bias, underscoring the utility of data-driven approaches for transparency.

AB - In this work, we present an interactive data visualization dashboard developed for the 2025 VAST Challenge Mini-Challenge 2, which investigates stakeholder engagement and potential bias during council meetings. The dashboard integrates matrix-based visualizations, barplots, trend lines, boxplots, and tooltips to support exploratory analysis. Through the TROUT (tourism) and FILAH (fishing) datasets, we identify systematic sentiment differences aligned with each group’s sectoral interests—particularly when discussions involve their own industries (e.g., large-vessel fishing or tourism)—providing evidence of potential bias among council members (COOTEFOO). Incorporating the JOURNALIST dataset, which combines both perspectives, reveals a moderation of sentiment extremes when a broader, more balanced view is introduced. Overall, this paper demonstrates how interactive dashboards can effectively expose and contextualize institutional bias, underscoring the utility of data-driven approaches for transparency.

KW - Bias Detection

KW - Data Visualization Dashboard

KW - Matrix-Based Visualization

KW - Mini-Challenge 2

KW - VAST Challenge

UR - https://www.scopus.com/pages/publications/105031907424

U2 - 10.1109/VAST-Challenge69463.2025.00019

DO - 10.1109/VAST-Challenge69463.2025.00019

M3 - Conference contribution

AN - SCOPUS:105031907424

SP - 29

EP - 30

BT - Proceedings - 2025 IEEE Visual Analytics Science and Technology, VAST Challenge 2025

PB - IEEE

T2 - 2025 IEEE Visual Analytics Science and Technology, VAST Challenge 2025

Y2 - 3 November 2025 through 3 November 2025

ER -

Investigating Institutional Bias Through a Visualization Dashboard

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