NetworkNarratives: Data tours for visual network exploration and analysis

Wenchao Li; Sarah Schöttler; James Scott-Brown; Yun Wang; Siming Chen; Huamin Qu; Benjamin Bach

doi:10.48550/arXiv.2303.06456

NetworkNarratives: Data tours for visual network exploration and analysis

Wenchao Li, Sarah Schöttler, James Scott-Brown, Yun Wang, Siming Chen, Huamin Qu, Benjamin Bach

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

This paper introduces semi-automatic data tours to aid the exploration of complex networks. Exploring networks requires significant effort and expertise and can be time-consuming and challenging. Distinct from guidance and recommender systems for visual analytics, we provide a set of goal-oriented tours for network overview, ego-network analysis, community exploration, and other tasks. Based on interviews with five network analysts, we developed a user interface (NetworkNarratives) and 10 example tours. The interface allows analysts to navigate an interactive slideshow featuring facts about the network using visualizations and textual annotations. On each slide, an analyst can freely explore the network and specify nodes, links, or subgraphs as seed elements for follow-up tours. Two studies, comprising eight expert and 14 novice analysts, show that data tours reduce exploration effort, support learning about network exploration, and can aid the dissemination of analysis results. NetworkNarratives is available online, together with detailed illustrations for each tour.

Original language	English
Title of host publication	Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
Editors	Albrecht Schmidt, Kaisa Väänänen, Tesh Goyal, Per Ola Kristensson, Anicia Peters, Stefanie Mueller, Julie R. Williamson, Max L. Wilson
Publisher	ACM
Pages	1-15
Number of pages	15
ISBN (Electronic)	9781450394215
DOIs	https://doi.org/10.48550/arXiv.2303.06456 https://doi.org/10.1145/3544548.3581452
Publication status	Published - 19 Apr 2023
Event	2023 CHI Conference on Human Factors in Computing Systems - Hamburg, Germany Duration: 23 Apr 2023 → 28 Apr 2023

Conference

Conference	2023 CHI Conference on Human Factors in Computing Systems
Abbreviated title	CHI 2023
Country/Territory	Germany
City	Hamburg
Period	23/04/23 → 28/04/23

Keywords / Materials (for Non-textual outputs)

guided exploration
network visualization

Access to Document

LiEtalCHI2023NetworkNarrativesDataToursAccepted author manuscript, 8.79 MBLicence: Creative Commons: Attribution (CC-BY)

Cite this

Li, W., Schöttler, S., Scott-Brown, J., Wang, Y., Chen, S., Qu, H., & Bach, B. (2023). NetworkNarratives: Data tours for visual network exploration and analysis. In A. Schmidt, K. Väänänen, T. Goyal, P. O. Kristensson, A. Peters, S. Mueller, J. R. Williamson, & M. L. Wilson (Eds.), Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (pp. 1-15). Article 172 ACM. https://doi.org/10.48550/arXiv.2303.06456, https://doi.org/10.1145/3544548.3581452

Li, Wenchao ; Schöttler, Sarah ; Scott-Brown, James et al. / NetworkNarratives : Data tours for visual network exploration and analysis. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. editor / Albrecht Schmidt ; Kaisa Väänänen ; Tesh Goyal ; Per Ola Kristensson ; Anicia Peters ; Stefanie Mueller ; Julie R. Williamson ; Max L. Wilson. ACM, 2023. pp. 1-15

@inproceedings{d7ccebcf0a4f404ebaa018955b740553,

title = "NetworkNarratives: Data tours for visual network exploration and analysis",

abstract = "This paper introduces semi-automatic data tours to aid the exploration of complex networks. Exploring networks requires significant effort and expertise and can be time-consuming and challenging. Distinct from guidance and recommender systems for visual analytics, we provide a set of goal-oriented tours for network overview, ego-network analysis, community exploration, and other tasks. Based on interviews with five network analysts, we developed a user interface (NetworkNarratives) and 10 example tours. The interface allows analysts to navigate an interactive slideshow featuring facts about the network using visualizations and textual annotations. On each slide, an analyst can freely explore the network and specify nodes, links, or subgraphs as seed elements for follow-up tours. Two studies, comprising eight expert and 14 novice analysts, show that data tours reduce exploration effort, support learning about network exploration, and can aid the dissemination of analysis results. NetworkNarratives is available online, together with detailed illustrations for each tour.",

keywords = "guided exploration, network visualization",

author = "Wenchao Li and Sarah Sch{\"o}ttler and James Scott-Brown and Yun Wang and Siming Chen and Huamin Qu and Benjamin Bach",

year = "2023",

month = apr,

day = "19",

doi = "10.48550/arXiv.2303.06456",

language = "English",

pages = "1--15",

editor = "Albrecht Schmidt and Kaisa V{\"a}{\"a}n{\"a}nen and Tesh Goyal and Kristensson, {Per Ola} and Anicia Peters and Stefanie Mueller and Williamson, {Julie R.} and Wilson, {Max L.}",

booktitle = "Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems",

publisher = "ACM",

note = "2023 CHI Conference on Human Factors in Computing Systems, CHI 2023 ; Conference date: 23-04-2023 Through 28-04-2023",

}

Li, W, Schöttler, S, Scott-Brown, J, Wang, Y, Chen, S, Qu, H & Bach, B 2023, NetworkNarratives: Data tours for visual network exploration and analysis. in A Schmidt, K Väänänen, T Goyal, PO Kristensson, A Peters, S Mueller, JR Williamson & ML Wilson (eds), Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems., 172, ACM, pp. 1-15, 2023 CHI Conference on Human Factors in Computing Systems, Hamburg, Germany, 23/04/23. https://doi.org/10.48550/arXiv.2303.06456, https://doi.org/10.1145/3544548.3581452

NetworkNarratives: Data tours for visual network exploration and analysis. / Li, Wenchao; Schöttler, Sarah; Scott-Brown, James et al.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. ed. / Albrecht Schmidt; Kaisa Väänänen; Tesh Goyal; Per Ola Kristensson; Anicia Peters; Stefanie Mueller; Julie R. Williamson; Max L. Wilson. ACM, 2023. p. 1-15 172.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - NetworkNarratives

T2 - 2023 CHI Conference on Human Factors in Computing Systems

AU - Li, Wenchao

AU - Schöttler, Sarah

AU - Scott-Brown, James

AU - Wang, Yun

AU - Chen, Siming

AU - Qu, Huamin

AU - Bach, Benjamin

PY - 2023/4/19

Y1 - 2023/4/19

N2 - This paper introduces semi-automatic data tours to aid the exploration of complex networks. Exploring networks requires significant effort and expertise and can be time-consuming and challenging. Distinct from guidance and recommender systems for visual analytics, we provide a set of goal-oriented tours for network overview, ego-network analysis, community exploration, and other tasks. Based on interviews with five network analysts, we developed a user interface (NetworkNarratives) and 10 example tours. The interface allows analysts to navigate an interactive slideshow featuring facts about the network using visualizations and textual annotations. On each slide, an analyst can freely explore the network and specify nodes, links, or subgraphs as seed elements for follow-up tours. Two studies, comprising eight expert and 14 novice analysts, show that data tours reduce exploration effort, support learning about network exploration, and can aid the dissemination of analysis results. NetworkNarratives is available online, together with detailed illustrations for each tour.

AB - This paper introduces semi-automatic data tours to aid the exploration of complex networks. Exploring networks requires significant effort and expertise and can be time-consuming and challenging. Distinct from guidance and recommender systems for visual analytics, we provide a set of goal-oriented tours for network overview, ego-network analysis, community exploration, and other tasks. Based on interviews with five network analysts, we developed a user interface (NetworkNarratives) and 10 example tours. The interface allows analysts to navigate an interactive slideshow featuring facts about the network using visualizations and textual annotations. On each slide, an analyst can freely explore the network and specify nodes, links, or subgraphs as seed elements for follow-up tours. Two studies, comprising eight expert and 14 novice analysts, show that data tours reduce exploration effort, support learning about network exploration, and can aid the dissemination of analysis results. NetworkNarratives is available online, together with detailed illustrations for each tour.

KW - guided exploration

KW - network visualization

UR - http://www.scopus.com/inward/record.url?scp=85160003748&partnerID=8YFLogxK

U2 - 10.48550/arXiv.2303.06456

DO - 10.48550/arXiv.2303.06456

M3 - Conference contribution

AN - SCOPUS:85160003748

SP - 1

EP - 15

BT - Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

A2 - Schmidt, Albrecht

A2 - Väänänen, Kaisa

A2 - Goyal, Tesh

A2 - Kristensson, Per Ola

A2 - Peters, Anicia

A2 - Mueller, Stefanie

A2 - Williamson, Julie R.

A2 - Wilson, Max L.

PB - ACM

Y2 - 23 April 2023 through 28 April 2023

ER -

Li W, Schöttler S, Scott-Brown J, Wang Y, Chen S, Qu H et al. NetworkNarratives: Data tours for visual network exploration and analysis. In Schmidt A, Väänänen K, Goyal T, Kristensson PO, Peters A, Mueller S, Williamson JR, Wilson ML, editors, Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. ACM. 2023. p. 1-15. 172 doi: 10.48550/arXiv.2303.06456, 10.1145/3544548.3581452

NetworkNarratives: Data tours for visual network exploration and analysis

Abstract / Description of output

Conference

Keywords / Materials (for Non-textual outputs)

Access to Document

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Fingerprint

semi-automatic data tours to support data exploration and visualisation literacy for novice analysts

Cite this

NetworkNarratives: Data tours for visual network exploration and analysis

Abstract / Description of output

Conference

Keywords / Materials (for Non-textual outputs)

Access to Document

Other files and links

Fingerprint

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semi-automatic data tours to support data exploration and visualisation literacy for novice analysts

Cite this