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Review of Vivid and Engaging: Effects of Interactive Data Visualization on Perceptions and Attitudes about Social Issues
By Cindy Royal, Professor
September 18, 2023
A new research article in Digital Journalism caught my attention recently. “Vivid and Engaging: Effects of Interactive Data Visualization on Perceptions and Attitudes about Social Issues” by Haiyan Jia of Lehigh University and S. Shyam Sundar of Penn State University deals with the effectiveness of interactive data visualizations. I have long studied data journalism and been a fan of interactive data presentations, the likes of which Propublica (see Dollars for Docs) and New York Times (see Is It Better to Rent or Buy?) have created. But over the years, I started hearing from various data journalists across news organizations that interactive charts, graphs and maps took too much time and didn’t add to users’ comprehension. They more frequently settled on static graphics to present data with stories. I always balked at this logic. I felt that interactivity gave the user a way to customize the information for their specific situation, allowing them to better use it in making decisions. Not to mention, I always felt that interactivity had the possibility of keeping a user on the site longer, tinkering with its features. Plus, I enjoyed teaching students how to make interactive data presentations. I am happy to see that the current study provides some proof that my instincts were correct.
Jia and Sundar explain that “individuals’ data use is constrained by their data literacy” (p. 2). They introduce exemplification theory (Zillman, 2002), which explains that users’ perceptions are often influenced by exemplars used in stories – anecdotes and quotations – rather than what the data shows. They use the example of an article on financial struggles of farmers that has mostly negative quotes related to the situations, but a statistical data point indicates only a third of farmers are financially struggling. The quotes are more likely to color the situation as more widespread than it actually is. I have often explained to students that interviews and quotes can only reflect the people they represent. How users are able to more effectively apply the information is to allow them to customize it for themselves. Interactive visualizaitons that allow users to change data based on location, economic variables, ethnicity, gender and more provide that possibility.
Much of the conventional wisdom associated with visualization comes from the “vividness” of the examples and the idea that data (or what the authors often call “baserate information”) is boring and dull. Data is difficult to picture in one’s mind, so it doesn’t evoke emotion as effectively as exemplars. Charts and graphs help, but when static visualizations were placed with text, they did not counter the exemplification effects. Visual features like video and animation (Diao and Sundar 2004) were noted as useful, but these scholars wanted to test the engagement qualities of interactive visualizations. Their first hypothesis was “Interactive visualization of baserate information, compared to static visualization or textual description, will lead to higher perceptions of presentational vividness and message vividness, as well as higher level of accuracy in issue perception.”
The authors introduce the relationship between interactivity and engagement and the idea of being “active,” long addressed in media research (for example, McMillian & Hwang, 2002; Deuze, 2004; Sundar, 2007; Bruns, 2009). They conceptualize interactivity as it relates to both platform affordances (perceptual bandwidth) and message exchange (perceptual contingency). Users’ perception of an interactive visualization can be described as the sum of their activities using it. “As a result, users are likely to view the visualization as an outcome of their own interaction history, the detailed information as contingent upon their requests and inputs, and the interface as interactive and responsive” (p. 6). Engagement is the crux of the second hypothesis, “Interactive visualization of baserate information, compared to static visualization or textual description, will lead to higher levels of perceptual bandwidth, perceived contingency, and user engagement, as well as a higher level of accuracy in issue perception.”
The method chosen was an experiment introducing two different news stories, one about climate change and one about same-sex marriage. Each article was presented in one of three ways: static visualization, interactive visualization, or textual description. They also varied the distribution of exemplars to be either proportionally consistent, or inconsistent, with the baserate information for a 2 (Exemplar Distribution) × 3 (Presentational Format) × 2 (News Topic) mixed-design experiment. The interactive visualization presented the same baserate information as shown in static visualization and textual descriptions, but it afforded a variety of interaction techniques (i.e., click, mouseover, drag), through which participants could perform actions such as data selection, visualization modification, etc.
169 research participants were recruited, with 111 coming from an undergraduate population and the balance from Amazon Mechanical Turk (MTurk), in an effort to provide more diversity. A range of variables were measured including perceived vividness (exemplar, presentational, message), perceptual bandwidth, perceived contingency, user engagement (time, absorption, fun), information processing (systematic, heuristic), recall (baserate, exemplar), issue perception, personal attitude and behavioral intention.
They showed that the perceived presentational vividness was significantly higher for the interactive and static visualization conditions than the textual description condition. Perceived message vividness was highest for the interactive visualization condition, compared to static visualization and textual description conditions. “Going one step beyond the static visualization that is predominantly used in today’s online news content, this study contrasts interactive visualization to static charts and text, providing theoretical and practical implications for journalism research and practice, as well as the design of effective online tools and interfaces for presenting data-based information” (p. 15).
The authors also explain why this could be so, through both platform features and engagement. “The findings from this study have shown that perceptual bandwidth and perceived contingency both play a key mediating role underlying the interactivity effect, underscoring the fact that interactive data visualization influences readers through both the presence of interactive features and the back-and-forth information exchange that it engenders” (p. 16).
In regard to issue perception, the study found that increased systematic information processing was the result of more perceived vividness and engagement. “This study reveals that heightened user engagement as a result of interface interactivity is in fact positively associated with systematic processing“ (p. 17).
There is a lot more to digest in terms of their method and presentation of results, so be sure to reference the full article. But for journalistic practice, the piece has interesting recommendations regarding design and development of interfaces resulting in user benefits and traffic generation. “Its findings signify the effects of technological design in informing and engaging today’s increasingly tech-savvy readers. As most individuals consume news online and from social media, well-designed interactive data visualization is readily shareable and likely to generate traffic to different channels of news distribution“ (p.17). I came to a similar conclusion in a piece I wrote in 2010, identifying that news consumers have a growing expectation of engagement features in the content they consume based on their social media activities. I further identified news organizations' role as architects of user experience (Royal, 2012).
Overall, the results provide new insight into limiting the power of exemplars. “This study revisits exemplification theory and shows evidence that interactive visualization can counteract exemplification effects by engaging individuals with visual presentation, the message, and information processing” (p.19). My take from this is that news organizations may want to reconsider their preference for static visualizations over interactive. This will present challenges, however, in hiring personnel with the skills to develop engaging interfaces. As such, these results also introduce implications for the increased role of interactive visualization in media education. This will be particularly relevant in teaching data journalism and product management, as complex interactive visualizations require teams with varied skill sets in data, design and user experience. But the opportunities to better address audience needs for information and issue perception are worthy.
There is certainly more work to be done in better understanding the usefulness of interactive visualizations. This study used two specific social issues to frame news stories and the sample was not as diverse as it could be, particularly from a global standpoint. From a cultural perspective, implementing choices in design and presentation goes counter to the role journalists have traditionally played in controlling messages. Also, the exact nature of the interactivity should be better understood. A simple graphic in which hovering over a pie slice reveals information is different than a chart that is completely reconstructed via a dropdown for year or other variable or a creative visual interface that has more game-like qualities of interaction.
Finally, the authors identify the study’s relevance to media effects scholarship. “Interactivity, as a feature of the medium, seems to diminish the effects of message features by allowing users to customize and scrutinize the content more deeply, thus challenging scholars to rethink media effects research in this era of interactive media. In sum, it would not be an exaggeration to say that an understanding of interactivity’s effects on the formation of individual perceptions and attitudes is essential in today’s communication studies” (p.19). This study also extends ongoing scholarship in the areas of data journalism and media product management. Earlier this year, I introduced a product-engagement model that identified the role of platform interface, data model and algorithms in influencing engagement, circling back to audience attitudes and behaviors (Royal, 2023). I hope the results of the current study inspire new creativity in data presentation and engagement.
The full study is online at https://www.tandfonline.com/doi/abs/10.1080/21670811.2023.2250815.
References
Bruns, Axel. 2009. “From Reader to Writer: Citizen Journalism as News Produsage.” In International Handbook of Internet Research, edited by Hunsinger, J., Klastrup, L., and Allen, M., 119–133. Dordrecht: Springer.
Deuze, M. 2004. “What is Multimedia Journalism?” Journalism Studies 5 (2): 139–152.
Diao, Fangfang, and S. Shyam Sundar. 2004. “Orienting Response and Memory for Web
Advertisements: Exploring Effects of Pop-Up Window and Animation.” Communication Research 31 (5): 537–567.
McMillan, Sally J., and Jang-Sun Hwang. 2002. “Measures of Perceived Interactivity: An Exploration of the Role of Direction of Communication, User Control, and Time in Shaping Perceptions of Interactivity.” Journal of Advertising 31 (3): 29–42.
Royal, Cindy. 2012. “Making Media Social: News as User Experience - Revisited,” in The Future of News. An Agenda of Perspectives - Second Edition. Edited by Hinsley, A. W., Kaufhold, K., & Lewis, S. C. Cognella.
Royal, C. 2023. “Design Implications for a Burgeoning Digital Product Ecosystem: Roles, Culture and Engagement.” Digital Journalism, 11(3), 587-594.
Sundar, S. Shyam. 2007. “Social Psychology of Interactivity in Human-Website Interaction.” In The Oxford Handbook of Internet Psychology, edited Adam N. Joinson, Katelyn Y. A. McKenna, Tom Postmes, and Ulf-Dietrich Reips, 89–104. Oxford, UK: Oxford University Press.
Zillmann, Dolf. 2002. “Exemplification Theory of Media Influence.” In Media Effects: Advances in Theory and Research, edited by J. Bryant and D. Zillmann, 29–52. Mahwah, NJ: Erlbaum.