Can Datavis Make Unpalatable Data More Enjoyable?

In the autumn of 2020, I came across a news article from The Guardian discussing audience beliefs and responses to graphs, charts, and maps. The article, titled “Facts v feelings: how to stop our emotions misleading us,” posits that if the title of the graph makes a claim about, for example, climate change, it attracts attention and engagement not because it is true or false, but because of the way people feel about the issue. 

I believe this to some extent, given my PhD research on audience responses to datavis about climate change, where I asked 34 study participants to provide emotional reactions to different types of climate-related data visuals. My work investigated elements of color, hand-drawings, animation, and interactivity using 13 different graphs, charts and maps. I sought to gather empirical evidence about whether and how these elements play into audiences’ engagement with the datavis. Based on my findings, I argue that design and visual style of datavis can be just as emotionally appealing as the subject matter or represented data itself.

The growing recognition of emotions in datavis

The increasing importance of datavis as a means of communicating information to the public has prompted visualisation designers to deliberately consider emotions in their work. For example, data journalist and illustrator Mona Chalabi suggested in 2016 that “there is no such thing as an emotionless data visualisation.” As she explained, datavis always has an emotive charge because emotions and feelings are often, consciously or not, embedded in the design decisions of the creators. On the other hand, Giorgia Lupi highlighted in 2017 datavis’ potential to evoke emotions and connect with people’s lives, transforming and simplifying quantitative data into something that can be both seen and felt.

Existing social science literature supports the idea that individuals respond emotionally, as well as rationally, to datavis. In the journal Sociology in 2017, U.K. researchers Helen Kennedy and Rosemary Hill identified emotional responses to various aspects of datavis, such as the visual style, the underlying data, subject matter, source or where the datavis is published, and skill levels for making sense of visualisation. As the authors point out, it was much easier for people to engage with datavis when they felt confident about their numeracy skills. Effectively, this means that people’s experiences and understanding of datavis depends on how much confidence they have. Other authors, including Catherine D’Ignazio, Rahul Bhargava, Jill Simpson, and Jonathan Gray, all explored the importance of emotions in datavis in their respective chapters within the book Data Visualization in Society.

Exploring emotive datavis features

Drawing on the work of Kennedy, Hill, and others, I investigated the emotional responses of Polish and British audiences to different datavis features, focusing on the following elements: color, hand-drawn elements, animation, and interactivity. These features were chosen based on their potential to evoke emotions in my research participants. While some relationships between these datavis features and the emotional responses to them seem logical and have been discussed by scholars and datavis designers (including Eric Margolis and Luc Pauwels in 2011; Lisa Charlotte Muth in 2018, Anna Feigenbaum and Aria Alamalhodaei 2020), there is still little empirical evidence about whether and how they shape and influence audiences’ engagements with datavis. I focused on climate change as a case study, investigating data produced or disseminated by six climate and environmental organisations from the UK and Poland including Carbon Brief UK, Climate Science Poland (Nauka o klimacie Polska), Greenpeace UK, Greenpeace Poland, WWF UK, and WWF Poland. 

The emotive power of color

Color emerged as the most emotive feature in climate change datavis. Participants often cited color as the initial aspect that attracted their attention, evoking positive emotions and a desire to explore the datavis further, even when they did not know what the image was about.

For example, one study participant, Aurora from Poland, described her experiences with the datavis Warming Stripes for Poland, which she encountered on Facebook: 

I remember flying somewhere, coming across this beautiful… scrolling on my phone and seeing bars in weird colors. I had no idea what was going on. I didn’t quite see the gradient. The colors passed through each other nicely. And I remember thinking it was so cool, pretty, and fascinating that I had to pause and look at it, not sure what I was looking at, thinking “What is this?” 

However, red, in particular, was often associated with warnings and evoked fear, reinforcing Muth’s argument that certain colors may intuitively carry certain metaphors in a given culture. 

Hand-drawn datavis: embracing intimacy and playfulness

Hand-drawn datavis or elements of datavis evoked strong positive emotional responses among my study participants. For example, Rachel based in the UK discussed the Mona Chalabi datavis of the annual increase of CO2 emission from 1850 until 2010 that she encountered on the Greenpeace UK Instagram account.

This graph, which is broken up into ten pieces/images, moved Rachel because of its visual form: “You could see there was like a story to tell, and I was interested to see how the graph would pan out, and it’s quite simple and the colors are quite playful. It doesn’t feel too serious, even though it’s about a serious topic.” 

The visual form of this and other hand-drawn datavis created a sense of intimacy and informality, making participants feel more connected to the information presented. This conforms with Simpson’s argument in her paper, Visualizing data: A lived experience regarding the impact of hand-drawn datavis on emotions. As the author argues, this kind of datavis can be more emotive as it is often presented “as imperfect and incomplete representations of a concept” and is “not associated with technical neutrality,” thus it appears more subjective. 

The hand-drawn datavises that I presented to my participants were often perceived as funny, playful, and relatable, which illustrate the point made by Feigenbaum and Alamalhodaei. Those authors distinguish between conventional datavis and graphic novels, such as hand-drawn datavis, which operate in different aesthetics and have the potential to humanise data by evoking positive associations and emotions.

Animation: evoking happiness and enlightenment

Participants expressed happiness and enlightenment when engaging with moving maps, charts, and graphs. In response to the question about particular elements of the datavis that made her feel emotional, Hawa from the UK answered that it is usually animation: 

Yeah, it makes me feel happier seeing them (…). Sometimes they can be moving – some charts, some graphs are moving charts or graphs so it makes me feel happier, more enlightened, triggers feelings of happiness because I am able to visually see and observe data that is important. Because it’s also about[…] climate change and I’m able to observe the data patterns over time which makes me feel quite powerful as well, because I’m in command of, you know, understanding what the data is trying to say to us. 

Similar to Hawa, many participants were drawn to animated datavis and felt pleasure derived from watching the animation that gradually satisfied their curiosity, as they explained later when asked about their emotions. 

Interactivity: fostering engagement and exploration

Interactivity, in particular, was related to excitement and joy, offering participants the opportunity to explore data independently and empowering them to command their understanding of the information. This aligns with Andy Kirk’s argument in his 2012 book, A Handbook for Data Driven Design, that datavis can perform distinct functions, such as explaining or inviting exploration. 

Some climate datavis such as Warming stripes not only provided an explanatory picture of the data but also facilitated visual exploration, which significantly increased the participants’ emotional engagement. The majority participants who responded to interactive datavis enjoyed the experience and ability to independently search for data on interactive datavis. It encouraged them to spend more time exploring the datavis and expanding their knowledge, not only about their close surroundings but also other countries with which they had no personal ties. When pressed further on why the interactive datavis Warming stripes for Poland was so exciting for her, Natalia, based in Poland, commented while exploring the datavis at the same time: “And because they’re so interactive, it’s amazing, I love it. I’d just stay here and look at different countries. I’m gonna look at other ones…” This suggests that most people like datavis that invite exploration and are willing to devote more attention to them.

The appeal of visual form despite unsettling data

As discussed in this article, one of the key findings that emerged from my research was the powerful emotional impact of the design and visual style of datavis. Importantly, despite encountering frightening and distressing data related to climate change, many participants reported experiencing positive emotions such as joy, satisfaction, and a sense of playfulness right from the outset of their interaction with different datavis features explored earlier. This intriguing contradiction highlights the potential of the visual form to evoke emotions that seemingly transcend the seriousness of the represented data, in this case, climate change statistics. However, it is important to note that other factors matter as well, such as the individual’s interest in and orientation to the issue at hand, which contribute significantly to this emotional response.

This finding holds significant implications, particularly when considering the potential consequences of negative emotions caused by climate change or related data. Research by Chartles Ogunbode and colleagues published in the journal Current Psychology in 2021 has shown that negative emotions linked to climate change can have adverse effects on people’s mental health, even leading to symptoms of insomnia. Therefore, the capacity of the visual form in datavis to elicit positive emotions becomes a noteworthy aspect in shaping individuals’ experiences with climate change data. In public discourse and media coverage, negative emotions tend to dominate discussions surrounding climate change, notes a 2013 study in the journal Global Environmental Change. Thus, the ability of datavis to evoke positive emotions like joy and satisfaction offers a fresh perspective on how we engage with challenging data.

The findings contribute substantially to ongoing discussions among datavis designers and scholars and prompt reflection on the consequences of using datavis to present challenging information. The findings suggest that datavis possesses the potential to transform unpalatable data, such as climate change statistics, into a more enjoyable experience for audiences. This raises an essential question about whether this is what datavis designers or experts want, and whether there are consequences. For example, would datavis mobilise people to act if they were all simply enjoyable? (I also attempted to delve into this question in my study, published in Significance, The Royal Statistical Society’s journal.)

However, further research in this area is warranted to fully understand the broader impact of datavis on emotional engagement and decision-making. By delving deeper into how datavis influences emotional responses and decision-making, we can gain valuable insights into how to best design datavis to effectively communicate complex and sensitive information.

Monika Fratczak headshot
Monika Fratczak

Monika is currently working as a teaching associate in the Department of Sociological Studies and a postdoctoral researcher on the Patterns in Practice project in the Information School at the University of Sheffield. She completed her PhD research in 2022, focusing on emotional responses and the potential for democratic participation through data visualization about climate change in two different national contexts.