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REVIEW 4 major objections 6 minor 80 references

Understanding the Impact of Spatial Immersion in Web Data Stories

T0 review · 4 major / 6 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read Web data stories that feel spatially immersive are more interesting and persuasive than static or animated versions, but they are not more understandable or trustworthy.

desk verdict Solid empirical study of immersive web data stories, but the central claim outruns the data: no manipulation check and uncorrected multiple tests. read the letter →

arxiv 2411.18049 v2 pith:D5CWFODT submitted 2024-11-27 cs.HC

Seon Gyeom Kim , Juhyeong Park , Yutaek Song , Donggun Lee , Yubin Lee , Ryan Rossi , Jane Hoffswell , Eunyee Koh
show 1 more author
Tak Yeon Lee
This is my paper · ORCID
classification cs.HC
keywords datastorytellingspatialimmersionimmersiveanalyticsdesignpatternsscrollytellingcrowdsourceduserstudyreaderengagementpersuasiveness
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper asks whether web data stories that give readers a feeling of moving through a 3D data space actually change how readers respond. Drawing on a collection of 23 existing stories, the authors identify six recurring design patterns for evoking spatial immersion, then build four of their own stories in static, animated, and immersive versions. In a crowdsourced within-subjects study of 600 readers, the immersive versions were rated significantly more interesting and persuasive in several stories, and also more curiosity-provoking, but no condition was consistently easier to understand or more trustworthy. The paper's point is that spatial immersion is a usable design lever with real but selective effects: it buys engagement and persuasion while risking clarity and perceived honesty.

What carries the argument

The central object is a set of six design patterns (DP1–DP6) distilled from 23 spatially immersive web data stories: cinematic camera shots and transitions, intuitive encoding between phenomenon and representation, smoothly moving elements, direct manipulation of camera or visualization, realistic appearance, and dynamic dimension (switching between 2D and 3D views). These patterns are what the authors mean by spatial immersion in this web context — not head-mounted displays, but author-controlled virtual cameras, depth cues, and motion that make readers feel present in a data space. The patterns carry the argument twice: they are the taxonomy claimed to describe how practitioners create immersion, and they are the ingredient list used to build the four immersive experimental stories.

What would settle it

Run the same four stories with an added condition: one built with the immersive design patterns, and a separate 'decorative 3D' condition that uses the same 3D rendering but omits spatial cues such as camera motion or depth coherence. If readers rate both conditions equally interesting and persuasive, the spatial patterns are not the active ingredient; if perceived presence scores predict the interest advantage, immersion itself carries the effect. Measuring presence with a short questionnaire in the original design would also test the assumption directly.

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Extended reading notes

Core claim

The paper claims that the deliberate use of six design patterns — cinematic camera shots and transitions, intuitive data representations, realism, naturally moving elements, direct manipulation of camera or visualization, and dynamic dimension — reliably evokes spatial immersion in web data stories, and that this immersion shifts reader experience in a specific way: it makes stories more interesting, more persuasive, and more likely to spark curiosity, without improving (and sometimes hurting) understanding and trust. The claim rests on a controlled comparison in which four data stories were each built in three variants that share text and data but differ only in visual design. Across the five cognitive factors measured, immersive variants received significantly more interest votes in DS1, DS2, and DS4 and more persuasiveness votes in DS1 and DS2, with no consistent winner on ease of understanding or trustworthiness.

Load-bearing premise

The immersive variants are treated as spatially immersive because they implement the six design patterns, but the study never measures whether readers actually experienced spatial immersion or presence, so the observed effects might stem from 3D novelty or visual fanciness rather than immersion itself.

Editorial extensions

If this is right

  • Designers who want readers to find a story engaging and persuasive can add camera-driven 3D scenes, realistic textures, and natural motion without sacrificing the underlying text content.
  • For facts that must be understood precisely or trusted fully, static or animated 2D presentations remain the safer choice, and immersion should be reserved for topics where comprehension is already easy.
  • Hybrid designs that alternate clear 2D views with immersive 3D scenes may combine the engagement gains with the understanding and trust of simpler presentations.
  • Future authoring tools could expose these patterns as high-level primitives, since the authors estimate that building the immersive variant accounted for roughly 90 percent of development time.
  • The six patterns give researchers a vocabulary for describing and comparing immersive web stories beyond the specific examples collected.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The study does not measure whether readers actually felt spatially immersed, so if the interest and persuasion gains come from 3D novelty or animation rather than spatial immersion itself, the proposed mechanism would need revision.
  • A direct test is possible: add a presence or immersion questionnaire, or include a condition with 3D visuals that deliberately omit the spatial patterns, and see whether the measured advantage tracks perceived immersion.
  • The selective results suggest a cost-benefit model: immersion raises attention and emotional engagement while also raising reading cost and suspicion, so its net value depends on the story's goal rather than on immersion alone.
  • The pattern list is a snapshot of pre-2022 practice, and newer techniques such as VR-compatible scrollytelling suggest that the taxonomy will likely expand.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 6 minor

Summary. This paper investigates spatial immersion in web data stories. The authors collect 23 real-world data stories, identify six design patterns that purportedly promote spatial immersion, and then construct four new data stories, each in three variants (static, animated, immersive). A crowdsourced within-subjects study (N=600) compares the variants on five self-reported factors: interest, ease of understanding, persuasiveness, trustworthiness, and curiosity. The authors report that immersive variants received significantly more interest votes in DS1, DS2, and DS4, and more persuasiveness votes in DS1 and DS2, while no variant was consistently more understandable or trustworthy. Open-ended comments are analyzed qualitatively into four themes, leading to design implications and suggestions for authoring tools.

Significance. If the empirical claims withstand scrutiny, the paper offers a useful design vocabulary for immersive web data storytelling and one of the few controlled comparisons of static, animated, and immersive variants. The strengths are the systematic collection of 23 stories, the construction of four matched stimulus sets, the counterbalanced within-subjects design, and the qualitative analysis of participant comments. The authors also provide an openly accessible demo site, which supports reproducibility of the materials. However, the current analysis does not yet support the central causal interpretation about spatial immersion because the study never measures experienced immersion and the statistical reporting is incomplete; these issues need to be addressed before the paper's main claims can be accepted.

major comments (4)
  1. [V-D, Fig. 6] The quantitative results rest on 60 one-sample Wilcoxon signed-rank tests (5 factors × 4 stories × 3 pairwise comparisons) with no multiple-comparison correction. At α = 0.05, one would expect roughly three false positives by chance, so some of the highlighted significant results may be spurious. The paper also reports only significance stars rather than exact p-values, effect sizes, or confidence intervals. I recommend reporting exact test statistics and p-values, adding effect sizes (e.g., rank-biserial correlation), and applying a correction such as Benjamini–Hochberg, or at least justifying the uncorrected analysis.
  2. [V-B and V-D] The procedure states that participants answered three knowledge-check questions after reading the first condition, but the paper never reports or analyzes these data. Since ease of understanding is measured only through a self-reported Likert item, the objective knowledge-check responses could provide important convergent evidence about comprehension. The omission is especially noticeable because the authors explicitly excluded memorability due to carryover concerns, suggesting they were aware of objective measures; the collected knowledge-check data should be analyzed and reported, or their absence should be explained.
  3. [IV, V-D, VI-D] The immersive condition is assumed to evoke spatial immersion because it implements the six design patterns, but no manipulation check of perceived spatial immersion or presence is reported. The animated condition controls for animation and dynamic transitions, but it does not control for 3D appearance or visual novelty. Participant comments quoted in V-E describe the immersive variants as 'fancy 3D visual' and 'almost an adventure,' which suggests engagement and novelty, not verified spatial presence. The paper's own limitation section (VI-D) defers measuring immersion to future work ('Future work could measure the degree of immersion by gathering eye movements or task completion time'), which is insufficient for the central RQ2 claim that spatial immersion affects the reader's experience. Without a presence or immersion measure, the observed effects on interest and persuasion could be attributed to 3D visual spectacle rather than to spatial immersion per se.
  4. [Abstract, IV-V] The abstract and conclusion state that 'data stories with the design patterns for spatial immersion' are more interesting and persuasive, but the experiment only compares three holistic variants, with each immersive story bundling two to four patterns. No pattern-level decomposition or manipulation check isolates the effect of the six-pattern set, and the patterns themselves were derived from the same collection of stories that guided the construction of the immersive stimuli. The causal attribution to the six patterns is therefore broader than what the experiment directly supports; the paper should either soften this claim or add an analysis that addresses the pattern-level contribution.
minor comments (6)
  1. [II-A] There is a typo in 'cognitive absorbtion' in the related work section; the reference title uses 'Absorption'.
  2. [Fig. 6 caption] The caption says the bar charts are 'linearly concatenated,' which is unclear; please explain the arrangement and explicitly define what the asterisk denotes.
  3. [V-D] The claim that 'More than half of the participants in DS1, DS2, and DS3 rated extremely positive to the immersive stories when compared to the static' is not quantified; please provide exact counts or percentages.
  4. [IV-C] The 'Kenny and Becker's VR content' reference appears only as a footnote URL; a formal citation would be more appropriate.
  5. [Table I] The source name 'Visual Ciannamon' appears to be a typo for 'Visual Cinnamon.'
  6. [VI-D] Eye movements and task completion time are behavioral proxies, not direct measures of experienced immersion; in future work, a validated presence questionnaire would be a more direct manipulation check.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity; the design-pattern taxonomy, stimulus construction, and user-rated outcomes are independent, with only a construct-validity gap about measuring immersion.

full rationale

The paper contains no mathematical derivation, no fitted parameters, and no load-bearing self-citation. The six design patterns are a qualitative taxonomy extracted from 23 collected stories (Section III-C), and the four immersive variants are then built using those patterns (Section IV). This is not a circular reduction: the study outcomes (interest, ease of understanding, persuasiveness, trustworthiness, curiosity) are independently collected user ratings, not definitions or re-statements of the design patterns, and the results were not forced by construction. For example, immersive stories were not rated more understandable or trustworthy, and in DS3 the animated variant outperformed the immersive on persuasiveness, so the outcome was genuinely falsifiable. The paper never measures perceived spatial immersion, and it explicitly defers this in Section VI-D: 'Future work could measure the degree of immersion by gathering eye movements or task completion time after immersive experience.' That absence is a genuine construct-validity threat when attributing the observed interest and persuasion effects to spatial immersion rather than 3D novelty or visual fanciness, but it is an external-validity or correctness concern, not circularity. The abstract's claim about 'data stories with the design patterns for spatial immersion' is an empirical claim about designed stimuli and user responses, not a statement whose truth is guaranteed by the way the stimuli were defined. No uniqueness theorem, ansatz-smuggling citation, or renamed-known-result pattern is present. Honest non-finding: no significant circularity.

Assumptions & free parameters 0 free parameters · 3 assumptions · 0 invented entities

The paper introduces no free parameters or invented physical entities. Its main conceptual constructs are the six design patterns, which are treated as a reusable taxonomy rather than new entities. The key unstated premises are measurement assumptions: that Likert ratings capture the target constructs and that the immersive variants actually evoke spatial immersion.

assumptions (3)
  • domain assumption Self-reported Likert comparisons validly measure the five cognitive factors (interest, ease of understanding, persuasiveness, trustworthiness, curiosity).
    Section V-C relies on participants' subjective relative ratings as direct measures of these constructs, without validation against behavioral measures.
  • domain assumption The six design patterns extracted from 23 stories are sufficient to operationalize spatial immersion in the four experimental stories.
    Section IV builds the immersive conditions directly from the design patterns, but Section V includes no manipulation check for perceived spatial immersion.
  • domain assumption The 23-story snowball sample is representative of web data stories with spatial immersion.
    Section III-A describes snowball sampling from selected news outlets and blogs; Section VI-D acknowledges the collection only covers stories published before 2022.

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Cite this review

Pith. "Pith review of Understanding the Impact of Spatial Immersion in Web Data Stories." pith.science (2026). https://pith.science/paper/D5CWFODT

@misc{pith2026241118049,
  author       = {Pith},
  title        = {Pith review of: Understanding the Impact of Spatial Immersion in Web Data Stories},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/D5CWFODT}},
  note         = {Machine review of arXiv:2411.18049}
}
read the original abstract

An increasing number of web articles engage the reader with the feeling of being immersed in the data space. However, the exact characteristics of spatial immersion in the context of visual storytelling remain vague. For example, what are the common design patterns of data stories with spatial immersion? How do they affect the reader's experience? To gain a deeper understanding of the subject, we collected 23 distinct data stories with spatial immersion, and identified six design patterns, such as cinematic camera shots and transitions, intuitive data representations, realism, naturally moving elements, direct manipulation of camera or visualization, and dynamic dimension. Subsequently, we designed four data stories and conducted a crowdsourced user study comparing three design variations (static, animated, and immersive). Our results suggest that data stories with the design patterns for spatial immersion are more interesting and persuasive than static or animated ones, but no single condition was deemed more understandable or trustworthy.

Figures

Figures reproduced from arXiv: 2411.18049 by the authors.

Figure 1
Figure 1. DS1 shows bar charts comparing food consumption of two cities. To visually connect scenes in the narrative, the [PITH_FULL_IMAGE:figures/full_fig_p007_1.png] view at source ↗
Figure 2
Figure 2. DS2 visualizes how the household income distributions changed between 2009 and 2019, in relation to the change points. While the [PITH_FULL_IMAGE:figures/full_fig_p008_2.png] view at source ↗
Figure 3
Figure 3. DS3 compares the three economic downturns during the pandemic, and how quickly they got recovered. While the [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figures from the paper (3 more)
Figure 4
Figure 4. Figure 4: DS4 visualizes the impact of historical events on the mortality rates in France. (A) When introducing the heatmap, the [PITH_FULL_IMAGE:figures/full_fig_p009_4.png]
Figure 5
Figure 5. Figure 5: The within-subjects study procedure and the questionnaire page [PITH_FULL_IMAGE:figures/full_fig_p010_5.png]
Figure 6
Figure 6. Figure 6: A group of frequency bar charts showing participant ratings on the cognitive factors for each story. We linearly concatenated bar charts of three [PITH_FULL_IMAGE:figures/full_fig_p011_6.png]

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Reference graph

Works this paper leans on

80 extracted references · 73 canonical work pages

  1. [1]

    Analyzing immersion,

    L. Ermi and F. M ¨ayr¨a, “Analyzing immersion,” Worlds in play: Inter- national perspectives on digital games research , vol. 21, p. 37, 2007. 11https://graphics.wsj.com/3d-nasdaq/ 12https://artsandculture.google.com/experiment/passage-of- water/dAElpEyEjuE9XQ 13https://threejs.org/docs/#manual/ko/introduction/How-to-create-VR- content JOURNAL OF LATEX CL...

    work page 2007

  2. [2]

    Immersion, engagement, and presence: A method for an- alyzing 3-d video games,

    A. McMahan, “Immersion, engagement, and presence: A method for an- alyzing 3-d video games,” in The video game theory reader. Routledge, 2013, pp. 67–86

    work page 2013

  3. [3]

    Ryan, Narrative as virtual reality 2: Revisiting immersion and interactivity in literature and electronic media

    M.-L. Ryan, Narrative as virtual reality 2: Revisiting immersion and interactivity in literature and electronic media . JHU press, 2015

    work page 2015

  4. [4]

    Measuring Presence in Virtual Environments: A Presence Questionnaire,

    B. G. Witmer and M. J. Singer, “Measuring Presence in Virtual Environments: A Presence Questionnaire,” Presence: Teleoperators and Virtual Environments, vol. 7, no. 3, pp. 225–240, 06 1998. [Online]. Available: https://doi.org/10.1162/105474698565686

    doi:10.1162/105474698565686 1998

  5. [5]

    Murray, Hamlet on the Holodeck: The Future of Narrative in Cyberspace

    J. Murray, Hamlet on the Holodeck: The Future of Narrative in Cyberspace . Free Press, 1997. [Online]. Available: https: //books.google.co.kr/books?id=bzmSLtnMZJsC

    work page 1997

  6. [6]

    A framework for immersive virtual environ- ments (five): Speculations on the role of presence in virtual environ- ments,

    M. Slater and S. Wilbur, “A framework for immersive virtual environ- ments (five): Speculations on the role of presence in virtual environ- ments,” Presence: Teleoperators & Virtual Environments, vol. 6, no. 6, pp. 603–616, 1997

    1997

  7. [7]

    The apparent reality of movies and emotional arousal: A study using physiological and self-report measures,

    B. Rooney, C. Benson, and E. Hennessy, “The apparent reality of movies and emotional arousal: A study using physiological and self-report measures,” Poetics, vol. 40, no. 5, pp. 405–422, 2012. [Online]. Available: https://www.sciencedirect.com/science/article/pii/ S0304422X12000502

    work page 2012

  8. [8]

    Immersion revisited: A review of existing definitions of immersion and their relation to different theories of presence,

    N. C. Nilsson, R. Nordahl, and S. Serafin, “Immersion revisited: A review of existing definitions of immersion and their relation to different theories of presence,” Human technology, vol. 12, no. 2, pp. 108–134, 2016

    work page 2016

Show all 80 references
  1. [9]

    A note on presence terminology,

    M. Slater, “A note on presence terminology,” Presence Connect, vol. 3, 01 2003

    2003

  2. [10]

    Linking and layout: Exploring the integration of text and visualization in storytelling,

    Q. Zhi, A. Ottley, and R. Metoyer, “Linking and layout: Exploring the integration of text and visualization in storytelling,” in Computer Graphics Forum, vol. 38, no. 3. Wiley Online Library, 2019, pp. 675– 685

    2019

  3. [11]

    Visual narrative flow: Exploring factors shaping data visualization story reading experiences,

    S. McKenna, N. Henry Riche, B. Lee, J. Boy, and M. Meyer, “Visual narrative flow: Exploring factors shaping data visualization story reading experiences,” in Computer Graphics Forum , vol. 36, no. 3. Wiley Online Library, 2017, pp. 377–387

    2017

  4. [12]

    Spatial immersion versus emotional immersion, which is more immersive?

    C. Zhang, A. Perkis, and S. Arndt, “Spatial immersion versus emotional immersion, which is more immersive?” in 2017 Ninth International Conference on Quality of Multimedia Experience (QoMEX) , 2017, pp. 1–6

    2017

  5. [13]

    Be the data: A new approach for lmmersive analytics,

    X. Chen, J. Z. Self, L. House, and C. North, “Be the data: A new approach for lmmersive analytics,” in 2016 Workshop on Immersive Analytics (IA), 2016, pp. 32–37

    2016

  6. [14]

    Embedded data represen- tations,

    W. Willett, Y . Jansen, and P. Dragicevic, “Embedded data represen- tations,” IEEE Transactions on Visualization and Computer Graphics , vol. 23, no. 1, pp. 461–470, 2017

    2017

  7. [15]

    Interactive Visual Analysis of Image-Centric Cohort Study Data,

    P. Klemm, S. Oeltze-Jafra, K. Lawonn, K. Hegenscheid, H. V ¨olzke, and B. Preim, “Interactive Visual Analysis of Image-Centric Cohort Study Data,” IEEE transactions on visualization and computer graphics, vol. 20, no. 12, pp. 1673–1682, Dec. 2014

    2014

  8. [16]

    Perception of Visual Variables on Tiled Wall-Sized Displays for Information Visualization Applications,

    A. Bezerianos and P. Isenberg, “Perception of Visual Variables on Tiled Wall-Sized Displays for Information Visualization Applications,” IEEE transactions on visualization and computer graphics , vol. 18, no. 12, pp. 2516–2525, Dec. 2012

    2012

  9. [17]

    More than telling a story: Transforming data into visually shared stories,

    B. Lee, N. H. Riche, P. Isenberg, and S. Carpendale, “More than telling a story: Transforming data into visually shared stories,” IEEE computer graphics and applications , vol. 35, no. 5, pp. 84–90, 2015

    2015

  10. [18]

    Narrative visualization: Telling stories with data,

    E. Segel and J. Heer, “Narrative visualization: Telling stories with data,” IEEE Transactions on Visualization and Computer Graphics , vol. 16, no. 6, pp. 1139–1148, 2010

    2010

  11. [19]

    Narrative visualization: Sharing insights into complex data,

    G. Dove and S. Jones, “Narrative visualization: Sharing insights into complex data,” 2012

    2012

  12. [20]

    Visualization rhetoric: Framing effects in narrative visualization,

    J. Hullman and N. Diakopoulos, “Visualization rhetoric: Framing effects in narrative visualization,” IEEE transactions on visualization and computer graphics, vol. 17, no. 12, pp. 2231–2240, 2011

    2011

  13. [21]

    Un- derstanding data videos: Looking at narrative visualization through the cinematography lens,

    F. Amini, N. Henry Riche, B. Lee, C. Hurter, and P. Irani, “Un- derstanding data videos: Looking at narrative visualization through the cinematography lens,” in Proceedings of the 33rd Annual ACM conference on human factors in computing systems , 2015, pp. 1459– 1468

    2015

  14. [22]

    The concept of flow,

    M. Csikszentmihalyi, J. Nakamura, and M. Csikszentmihalyi, “The concept of flow,” Flow and the foundations of positive psychology: The collected works of Mihaly Csikszentmihalyi , pp. 239–263, 2014

    2014

  15. [23]

    Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage,

    R. Agarwal and E. Karahanna, “Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage,” MIS quarterly, pp. 665–694, 2000

    2000

  16. [24]

    A grounded investigation of game immersion,

    E. Brown and P. Cairns, “A grounded investigation of game immersion,” in CHI’04 extended abstracts on Human factors in computing systems , 2004, pp. 1297–1300

    2004

  17. [25]

    Towards a taxonomy of virtual reality user interfaces,

    M. K. Coomans and H. J. Timmermans, “Towards a taxonomy of virtual reality user interfaces,” in Proceedings. 1997 IEEE Conference on Information Visualization (Cat. No. 97TB100165) . IEEE, 1997, pp. 279–284

    1997

  18. [26]

    Factors of immersion,

    N. Curran, “Factors of immersion,” The Wiley Handbook of Human Computer Interaction, vol. 1, pp. 239–254, 2018

    2018

  19. [27]

    The development and evaluation of a survey to measure user engagement,

    H. L. O’Brien and E. G. Toms, “The development and evaluation of a survey to measure user engagement,” Journal of the American Society for Information Science and Technology, vol. 61, no. 1, pp. 50–69, 2010

    2010

  20. [28]

    Adams and A

    E. Adams and A. Rollings, Fundamentals of game design (game design and development series) . Prentice-Hall, Inc., 2006

    2006

  21. [29]

    Narrative design patterns for data-driven storytelling,

    B. Bach, M. Stefaner, J. Boy, S. Drucker, L. Bartram, J. Wood, P. Ciuccarelli, Y . Engelhardt, U. Koeppen, and B. Tversky, “Narrative design patterns for data-driven storytelling,” in Data-driven storytelling. AK Peters/CRC Press, 2018, pp. 107–133

    2018

  22. [30]

    Cinematic techniques in narrative visualization,

    M. Conlen, J. Heer, H. Mushkin, and S. Davidoff, “Cinematic techniques in narrative visualization,” arXiv preprint arXiv:2301.03109 , 2023

    2023 arXiv

  23. [31]

    Communicating with motion: A design space for animated visual narratives in data videos,

    Y . Shi, X. Lan, J. Li, Z. Li, and N. Cao, “Communicating with motion: A design space for animated visual narratives in data videos,” in Proceedings of the 2021 CHI conference on human factors in computing systems, 2021, pp. 1–13

    2021

  24. [32]

    Kineticharts: Augmenting affective expressiveness of charts in data stories with animation design,

    X. Lan, Y . Shi, Y . Wu, X. Jiao, and N. Cao, “Kineticharts: Augmenting affective expressiveness of charts in data stories with animation design,” IEEE Transactions on Visualization and Computer Graphics , vol. 28, no. 1, pp. 933–943, 2021

    2021

  25. [33]

    From ‘wow’to ‘why’: Guidelines for creating the opening of a data video with cinematic styles,

    X. Xu, L. Yang, D. Yip, M. Fan, Z. Wei, and H. Qu, “From ‘wow’to ‘why’: Guidelines for creating the opening of a data video with cinematic styles,” in Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems , 2022, pp. 1–20

    2022

  26. [34]

    A characteri- zation of interactive visual data stories with a spatio-temporal context,

    B. Mayer, N. Steinhauer, B. Preim, and M. Meuschke, “A characteri- zation of interactive visual data stories with a spatio-temporal context,” in Computer Graphics Forum , vol. 42, no. 6. Wiley Online Library, 2023, p. e14922

    2023

  27. [35]

    E. R. Tufte, The Visual Display of Quantitative Information . USA: Graphics Press, 1986

    1986

  28. [36]

    Useful junk? the effects of visual embellishment on comprehension and memorability of charts,

    S. Bateman, R. L. Mandryk, C. Gutwin, A. Genest, D. McDine, and C. Brooks, “Useful junk? the effects of visual embellishment on comprehension and memorability of charts,” in Proceedings of the SIGCHI conference on human factors in computing systems , 2010, pp. 2573–2582

    2010

  29. [37]

    Storytelling in information visualizations: Does it engage users to explore data?

    J. Boy, F. Detienne, and J.-D. Fekete, “Storytelling in information visualizations: Does it engage users to explore data?” in Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, ser. CHI ’15. New York, NY , USA: Association for Computing Machin...

    2015

  30. [38]

    Immersive Visual Data Stories,

    P. Isenberg, B. Lee, H. Qu, and M. Cordeil, “Immersive Visual Data Stories,” in Immersive Analytics , K. Marriott, F. Schreiber, T. Dwyer, K. Klein, N. H. Riche, T. Itoh, W. Stuerzlinger, and B. H. Thomas, Eds. Cham: Springer International Publishing, 2018, pp. 165–184. [Onlin...

    2018 doi

  31. [39]

    Understanding the effectiveness of adaptive guidance for narrative visualization: a gaze-based analysis,

    O. Barral, S. Lall ´e, and C. Conati, “Understanding the effectiveness of adaptive guidance for narrative visualization: a gaze-based analysis,” in Proceedings of the 25th international conference on intelligent user interfaces, 2020, pp. 1–9

    2020

  32. [40]

    Dear pictograph: Investigating the role of personalization and immersion for consuming and enjoying visualizations,

    H. Romat, N. Henry Riche, C. Hurter, S. Drucker, F. Amini, and K. Hinckley, “Dear pictograph: Investigating the role of personalization and immersion for consuming and enjoying visualizations,” in Proceed- ings of the 2020 CHI Conference on Human Factors in Computing Systems, ...

    2020

  33. [41]

    Crowdsourcing user studies with mechanical turk,

    A. Kittur, E. H. Chi, and B. Suh, “Crowdsourcing user studies with mechanical turk,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems , ser. CHI ’08. New York, NY , USA: Association for Computing Machinery, 2008, p. 453–456. [Online]. Available: ht...

    2008

  34. [42]

    Explorable explanations,

    B. Victor, “Explorable explanations,” Online. http://worrydream. com/ExplorableExplanations, vol. 17, 2011

    2011

  35. [43]

    Three. js framework,

    B. Danchilla and B. Danchilla, “Three. js framework,” Beginning WebGL for HTML5, pp. 173–203, 2012

    2012

  36. [44]

    D 3 data-driven documents,

    M. Bostock, V . Ogievetsky, and J. Heer, “D 3 data-driven documents,” IEEE transactions on visualization and computer graphics , vol. 17, no. 12, pp. 2301–2309, 2011. JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2021 17

    2011

  37. [45]

    Vega- lite: A grammar of interactive graphics,

    A. Satyanarayan, D. Moritz, K. Wongsuphasawat, and J. Heer, “Vega- lite: A grammar of interactive graphics,” IEEE transactions on visual- ization and computer graphics , vol. 23, no. 1, pp. 341–350, 2016

    2016

  38. [47]

    Potentials of digital longforms in journalism. a survey among mobile internet users about the relevance of online devices, internet-specific qualities, and modes of payment,

    C. Wolf and A. Godulla, “Potentials of digital longforms in journalism. a survey among mobile internet users about the relevance of online devices, internet-specific qualities, and modes of payment,” Journal of Media Business Studies , vol. 13, no. 4, pp. 199–221, 2016. [Onlin...

    2016

  39. [48]

    Scrollytelling – an analysis of visual storytelling in online journalism,

    D. Seyser and M. Zeiller, “Scrollytelling – an analysis of visual storytelling in online journalism,” in2018 22nd International Conference Information Visualisation (IV) , 2018, pp. 401–406

    2018

  40. [49]

    Leveraging text- chart links to support authoring of data-driven articles with vizflow,

    N. Sultanum, F. Chevalier, Z. Bylinskii, and Z. Liu, “Leveraging text- chart links to support authoring of data-driven articles with vizflow,” in Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, 2021, pp. 1–17

    2021

  41. [50]

    So You Think You Can Scroll Talk

    J. Vallandingham, “So You Think You Can Scroll Talk.” [Online]. Available: https://vallandingham.me/think you can scroll.html

  42. [51]

    Automatic generation of unit visualization-based scrollytelling for impromptu data facts delivery,

    J. Lu, W. Chen, H. Ye, J. Wang, H. Mei, Y . Gu, Y . Wu, X. L. Zhang, and K.-L. Ma, “Automatic generation of unit visualization-based scrollytelling for impromptu data facts delivery,” in 2021 IEEE 14th Pacific visualization symposium (PacificVis). IEEE, 2021, pp. 21–30

    2021

  43. [52]

    Scrollyvis: Interactive visual authoring of guided dynamic narratives for scientific scrollytelling,

    E. M ¨orth, S. Bruckner, and N. N. Smit, “Scrollyvis: Interactive visual authoring of guided dynamic narratives for scientific scrollytelling,” IEEE Transactions on Visualization and Computer Graphics , 2022

    2022

  44. [53]

    What is scrollytelling?(+ its impact on digital content): An interview

    M. Pettersen, “What is scrollytelling?(+ its impact on digital content): An interview.”

  45. [54]

    The Scrollytelling Scourge,

    R. Kosara, “The Scrollytelling Scourge,” May 2016. [Online]. Available: https://eagereyes.org/blog/2016/the-scrollytelling-scourge

    2016

  46. [55]

    Snowball sampling,

    C. Parker, S. Scott, and A. Geddes, “Snowball sampling,” SAGE research methods foundations, 2019

    2019

  47. [56]

    What makes a data- gif understandable?

    X. Shu, A. Wu, J. Tang, B. Bach, Y . Wu, and H. Qu, “What makes a data- gif understandable?” IEEE Transactions on Visualization and Computer Graphics, vol. 27, no. 2, pp. 1492–1502, 2020

    2020

  48. [57]

    Canis: A high- level language for data-driven chart animations,

    T. Ge, Y . Zhao, B. Lee, D. Ren, B. Chen, and Y . Wang, “Canis: A high- level language for data-driven chart animations,” in Computer Graphics Forum, vol. 39, no. 3. Wiley Online Library, 2020, pp. 607–617

    2020

  49. [58]

    How to display data badly,

    H. Wainer, “How to display data badly,” The American Statistician , vol. 38, no. 2, pp. 137–147, 1984. [Online]. Available: http: //www.jstor.org/stable/2683253

    1984

  50. [59]

    Graphics and human information processing: A review of five books,

    S. M. Kosslyn, “Graphics and human information processing: A review of five books,” Journal of the American Statistical Association, vol. 80, no. 391, pp. 499–512, 1985. [Online]. Available: http://www.jstor.org/stable/2288463

    1985

  51. [60]

    Reading bar graphs: Effects of extraneous depth cues and graphical context

    J. M. Zacks, E. Levy, B. Tversky, and D. J. Schiano, “Reading bar graphs: Effects of extraneous depth cues and graphical context.” Journal of Experimental Psychology: Applied , vol. 4, pp. 119–138, 1998

    1998

  52. [61]

    Why happiness is becoming more expensive and out of reach,

    N. Glozier and R. Morris, “Why happiness is becoming more expensive and out of reach,” 2021. [Online]. Available: https://www.sydney.edu.au/news-opinion/news/2021/11/16/ why-happiness-is-becoming-more-expensive-and-out-of-reach-.html

    2021

  53. [62]

    How to tell stories using visualization,

    A. Figueiras, “How to tell stories using visualization,” in 2014 18th International Conference on Information Visualisation , 2014, pp. 18– 18

    2014

  54. [63]

    A deeper understanding of sequence in narrative visualization,

    J. Hullman, S. Drucker, N. H. Riche, B. Lee, D. Fisher, and E. Adar, “A deeper understanding of sequence in narrative visualization,” IEEE Transactions on visualization and computer graphics , vol. 19, no. 12, pp. 2406–2415, 2013

    2013

  55. [64]

    What makes a visualization memorable?

    M. A. Borkin, A. A. V o, Z. Bylinskii, P. Isola, S. Sunkavalli, A. Oliva, and H. Pfister, “What makes a visualization memorable?” IEEE trans- actions on visualization and computer graphics , vol. 19, no. 12, pp. 2306–2315, 2013

    2013

  56. [65]

    The persuasive power of data visualization,

    A. V . Pandey, A. Manivannan, O. Nov, M. Satterthwaite, and E. Bertini, “The persuasive power of data visualization,” IEEE transactions on visualization and computer graphics , vol. 20, no. 12, pp. 2211–2220, 2014

    2014

  57. [66]

    If looks could kill: The impact of different rhetorical styles on persuasive geocommunication,

    I. Muehlenhaus, “If looks could kill: The impact of different rhetorical styles on persuasive geocommunication,” The Cartographic Journal , vol. 49, no. 4, pp. 361–375, 2012

    2012

  58. [67]

    Structure and empathy in visual data storytelling: Evaluating their influence on attitude,

    J. Liem, C. Perin, and J. Wood, “Structure and empathy in visual data storytelling: Evaluating their influence on attitude,” in Computer Graphics Forum, vol. 39, no. 3. Wiley Online Library, 2020, pp. 277– 289

    2020

  59. [68]

    Interest development and its relation to curiosity: Needed neuroscientific research,

    S. E. Hidi and K. A. Renninger, “Interest development and its relation to curiosity: Needed neuroscientific research,” Educational Psychology Review, vol. 31, no. 4, pp. 833–852, 2019

    2019

  60. [69]

    Persuasive systems design: Key issues, process model, and system features,

    H. Oinas-Kukkonen and M. Harjumaa, “Persuasive systems design: Key issues, process model, and system features,” Communications of the Association for Information Systems , vol. 24, 03 2009

    2009

  61. [70]

    Calliope: Automatic visual data story generation from a spreadsheet,

    D. Shi, X. Xu, F. Sun, Y . Shi, and N. Cao, “Calliope: Automatic visual data story generation from a spreadsheet,” IEEE Transactions on Visualization and Computer Graphics , vol. PP, pp. 1–1, 10 2020

    2020

  62. [71]

    An evaluation of the impact of visual embellishments in bar charts,

    D. Skau, L. Harrison, and R. Kosara, “An evaluation of the impact of visual embellishments in bar charts,” in Computer Graphics Forum, vol. 34, no. 3. Wiley Online Library, 2015, pp. 221–230

    2015

  63. [72]

    Isotype visualization: Working memory, performance, and engagement with pictographs,

    S. Haroz, R. Kosara, and S. L. Franconeri, “Isotype visualization: Working memory, performance, and engagement with pictographs,” in Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems , ser. CHI ’15. New York, NY , USA: Association for Computin...

    2015

  64. [73]

    Showing data about people: A design space of anthropographics,

    L. Morais, Y . Jansen, N. Andrade, and P. Dragicevic, “Showing data about people: A design space of anthropographics,” IEEE Transactions on Visualization and Computer Graphics, vol. 28, no. 3, pp. 1661–1679, 2020

    2020

  65. [74]

    Measuring and defining the experience of immersion in games,

    C. Jennett, A. L. Cox, P. Cairns, S. Dhoparee, A. Epps, T. Tijs, and A. Walton, “Measuring and defining the experience of immersion in games,” International journal of human-computer studies, vol. 66, no. 9, pp. 641–661, 2008

    2008

  66. [75]

    Emerging and Recurring Data-Driven Storytelling Techniques: Analysis of a Curated Collection of Recent Stories,

    C. D. Stolper, B. Lee, N. Henry Riche, and J. Stasko, “Emerging and Recurring Data-Driven Storytelling Techniques: Analysis of a Curated Collection of Recent Stories,” Tech. Rep. MSR-TR-2016-14, Apr. 2016

    2016

  67. [76]

    Visualization authoring for data-driven storytelling,

    D. Ren, “Visualization authoring for data-driven storytelling,” Ph.D. dissertation, UC Santa Barbara, 2019

    2019

  68. [77]

    Imaxes: Immersive axes as embodied affordances for interactive multivariate data visualisation,

    M. Cordeil, A. Cunningham, T. Dwyer, B. H. Thomas, and K. Mar- riott, “Imaxes: Immersive axes as embodied affordances for interactive multivariate data visualisation,” in Proceedings of the 30th annual ACM symposium on user interface software and technology , 2017, pp. 71–83

    2017

  69. [78]

    Dxr: A toolkit for building immersive data visualizations,

    R. Sicat, J. Li, J. Choi, M. Cordeil, W.-K. Jeong, B. Bach, and H. Pfister, “Dxr: A toolkit for building immersive data visualizations,” IEEE transactions on visualization and computer graphics , vol. 25, no. 1, pp. 715–725, 2018

    2018

  70. [79]

    Cine-ai: Generating video game cutscenes in the style of human directors,

    I. Evin, P. H ¨am¨al¨ainen, and C. Guckelsberger, “Cine-ai: Generating video game cutscenes in the style of human directors,” Proceedings of the ACM on Human-Computer Interaction , vol. 6, no. CHI PLAY , pp. 1–23, 2022

    2022

  71. [80]

    Learning to capture a film-look video with a camera drone,

    C. Huang, Z. Yang, Y . Kong, P. Chen, X. Yang, and K.-T. T. Cheng, “Learning to capture a film-look video with a camera drone,” in 2019 international conference on robotics and automation (ICRA) . IEEE, 2019, pp. 1871–1877

    2019

  72. [81]

    The virtual cinematographer: A paradigm for automatic real-time camera control and directing,

    L.-w. He, M. F. Cohen, and D. H. Salesin, “The virtual cinematographer: A paradigm for automatic real-time camera control and directing,” in Seminal Graphics Papers: Pushing the Boundaries, Volume 2, 2023, pp. 707–714. A. Appendix: Data Story Links [S1] Pearce, A. (2018). How ...

    2018

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.